MIT News - Mathematics
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MIT News is dedicated to communicating to the media and the public the news and achievements of the students, faculty, staff and the greater MIT community.enMon, 30 Nov 2015 18:13:01 -0500Daniel Rothman awarded math prize for work on Earth's carbon cycle
http://news.mit.edu/2015/daniel-rothman-awarded-math-prize-1130
Professor of geophysics and co-director of the Lorenz Center at MIT honored with the 2016 American Mathematical Society Levi L. Conant Prize.Mon, 30 Nov 2015 18:13:01 -0500Helen Hill | EAPShttp://news.mit.edu/2015/daniel-rothman-awarded-math-prize-1130<p>MIT Professor Daniel Rothman has been awarded the 2016 Levi L. Conant Prize from the American Mathematical Society (AMS).</p>
<p>Rothman's work has contributed widely to our understanding of the organization of the natural environment, resulting in fundamental advances in subjects ranging from seismology and fluid flow to biogeochemistry and geobiology. He has also made significant contributions to research in statistical physics. Recent areas of focused interest include the dynamics of Earth’s carbon cycle, the co-evolution of life and the environment, and the physical foundation of natural geometric forms.</p>
<p>The citation for the Conant Prize, which honors his 2015 paper, "<a href="http://www.ams.org/journals/bull/2015-52-01/S0273-0979-2014-01471-5" target="_blank">Earth's Carbon Cycle: A Mathematical Perspective</a>," in the <em>Bulletin of the American Mathematical Society</em>, says: "Mathematics finds a place in Science by enunciating principles that at once classify, quantify and illuminate natural phenomena. This heuristic is often best displayed when phenomena are simple or at least isolated from external influences. In this sense, biological processes present a particular challenge for Mathematics because they are generally tapestries of confounding factors. It is nowadays common to approach such problems from a viewpoint that promotes data collection and data analysis as the pathway to knowledge. But, as Dan Rothman points out in this article, 'Data, however, require understanding'. Here, he gives us an understanding of the Earth's carbon cycle by applying classical ideas from applied mathematics to the data at hand.</p>
<p>"This article is especially timely as humanity grapples with the consequences of releasing trapped carbon by burning fossil fuels. The author, a geophysicist, concludes with an invitation to mathematicians to take up the challenge: 'Because the carbon cycle represents the coupling between life and the environment — metabolism at a global scale — its mathematical description inherits the difficulties of biology in addition to physical science. Thus, theoretical understanding of dynamics, so crucial to advancing knowledge of how the carbon cycle works, remains more qualitative than quantitative. Such problems present scientific opportunities with no shortage of social significance. Mathematics will surely play a central role in future progress.'</p>
<p>"But it isn't just the timeliness of the topic that draws us in and holds our interest. At every step the author takes care to explain the science as well as the mathematics involved in clear straightforward prose so that the entire article is accessible to a general mathematical audience. We often hear about Wigner's 'unreasonable effectiveness of Mathematics in the sciences', but it is not so often that we see this manifested in a beautiful exposition of a fundamental ingredient of our existence."</p>
<p>Rothman joined the MIT faculty in 1986, after receiving his BA in applied mathematics from Brown University and his PhD in geophysics from Stanford University. In 2011, Rothman and his colleague Kerry Emanuel co-founded MIT’s Lorenz Center, a privately funded interdisciplinary research center devoted to learning how climate works. He is a fellow of the American Physical Society and the American Geophysical Union.</p>
<p>Presented annually, the Conant Prize recognizes the best expository paper published in either the <em>Notices of the AMS</em> or the <em>Bulletin of the AMS</em> in the preceding five years. The prize will be awarded on Thursday, Jan. 7, 2016, at the Joint Mathematics Meetings in Seattle.</p>
Daniel RothmanAwards, honors and fellowships, Faculty, EAPS, School of Science, Mathematics, Environment, Carbon cycle, Lorenz CenterAn extreme close-up on heat transfer
http://news.mit.edu/2015/nanoscale-heat-transfer-1125
New formula identifies limits to nanoscale heat transfer, may help optimize devices that convert heat to electricity.Tue, 24 Nov 2015 23:59:59 -0500Jennifer Chu | MIT News Officehttp://news.mit.edu/2015/nanoscale-heat-transfer-1125<p>How much heat can two bodies exchange without touching? For over a century, scientists have been able to answer this question for virtually any pair of objects in the macroscopic world, from the rate at which a campfire can warm you up, to how much heat the Earth absorbs from the sun. But predicting such radiative heat transfer between extremely close objects has proven elusive for the past 50 years.</p>
<p>Now, MIT mathematicians have derived a formula for determining the maximum amount of heat exchanged between two objects separated by distances shorter than the width of a single hair. For any two objects situated mere nanometers apart, the formula can be used to calculate the most heat one body may transmit to another, based on two parameters: what the objects are made of, and how far apart they are.</p>
<p>The formula may help engineers identify optimal materials and designs for tuning small, intricately patterned devices, such as thermophotovoltaic surfaces that convert thermal energy into electrical energy, and cooling systems for computer chips.</p>
<p>As a demonstration, the scientists used their formula to calculate the maximum heat transfer between two nanometer-spaced metal plates, and found that the structures may be able to transmit orders of magnitude more heat than they currently achieve.</p>
<p>“This [formula] provides a target to say, ‘this is what we should be looking for,’ and compared to what we’ve seen so far in simple structures, there’s orders of magnitude more room for improvement for this kind of heat transfer,” says Owen Miller, a postdoc in the Department of Mathematics. “If that’s practically achievable, that could make a huge difference in, for example, thermophotovoltaics.”</p>
<p>Miller and his colleagues Steven Johnson, professor of applied mathematics at MIT, and Alejandro Rodriguez, assistant professor of electrical engineering at Princeton University, have published their results in <em>Physical Review Letters.</em></p>
<p><strong>Small scale, big effect</strong></p>
<p>Since the late 1800s, scientists have used the Stefan-Boltzmann law to calculate the maximum amount of heat one body can transmit to another. This maximum heat transfer depends only on the two bodies’ temperatures and can be reached only when both bodies are extremely opaque, absorbing all the heat that is radiated on them — a theoretical notion known as the blackbody limit.</p>
<p>However, for objects smaller than the wavelength of heat — about 8 micrometers — scientists’ established theories of heat transfer no longer apply. In fact, it appears that at the nanoscale, the amount of heat transmitted between objects actually exceeds that predicted by the blackbody limit, hundreds of times over.</p>
<p>As it turns out, when objects are extremely close together, heat flows not just as electromagnetic waves, but as evanescent waves — exponentially decaying waves that have little effect at the macroscale, as they typically die away before reaching another object. At the nanoscale, however, evanescent waves can play a large role in heat transfer, tunneling between objects and essentially releasing trapped energy in the form of extra heat. Only in the last few years have Johnson and others at MIT, including Homer Reid, an applied mathematics instructor; Gang Chen, the Carl Richard Soderberg Professor of Power Engineering and head of the Department of Mechanical Engineering; and Mehran Kardar, the Francis Friedman Professor of Physics; begun to predict and quantify heat transfer at the nanoscale.</p>
<p><strong>A surprisingly generalizable equation</strong></p>
<p>Miller and his colleagues derived a formula for determining the maximum heat transfer between two extremely close objects. To do so, they used an existing model that describes radiative heat transfer as electrical currents flowing within two objects. Such currents arise from each object’s fluctuating electric dipoles, or, its distribution of negative and positive charges.</p>
<p>Using this model as a framework, the team added two additional constraints: energy conservation, in which there is a limit to the amount of energy one body can absorb; and reciprocity, where each body may be treated as a source or receiver of heat. With this approach, the researchers derived a simple equation to calculate the maximum, or upper bound, of heat that two bodies may exchange at nanoscale separations.</p>
<p>The equation is surprisingly generalizable and can be applied to any pair of objects regardless of their shape. Scientists simply input two parameters into the equation: separation distance, and certain material properties of each object — namely, the maximum amount of electric current that can build up in a given material.</p>
<p>“Now we have a formula for the upper bound,” Johnson says. “Given the material and the separation you want, you’d just plug it into the formula and boom, you’re done — it’s very easy. Now you can go backwards and try to play with materials and optimize them.”</p>
<p>Johnson says engineers can use the formula to identify the best possible combination and orientation of materials for optimizing heat transfer in nanodevices such as thermophotovoltaics, which involves etching surfaces with very fine, intricate patterns to improve their heat-absorbing properties.</p>
<p>The team has done some preliminary work in exploring heat transfer between various materials at the nanoscale. Taking about 20 different materials from the periodic table — mostly metals — Miller calculated the maximum heat transfer between pairs of them, at extremely small separations.</p>
<p>“This is still ongoing work, but aluminum looks like it has a lot of potential if it can be designed properly,” Miller says. “It has to be designed properly in order to achieve the limit, which is why people haven’t seen large enhancements with such materials before, but this really opens up a new class of materials that may be used.”</p>
MIT mathematicians have identified the limits to heat flow at the nanoscale.Energy, Heat, Mathematics, Nanoscience and nanotechnology, Research, Solar, School of ScienceBose Grants fund bold and innovative visions
http://news.mit.edu/2015/bose-grants-fund-bold-innovative-visions-1124
Four high-risk, high-reward projects launch with support from Professor Amar G. Bose Research Grants.Tue, 24 Nov 2015 12:00:00 -0500Jessica Fujimori | MIT News correspondenthttp://news.mit.edu/2015/bose-grants-fund-bold-innovative-visions-1124<p>Magnetism-sensing worms, ancient violins, ionic liquids, and malaria microbes — these are the subjects of the latest research projects to be supported by the Professor Amar G. Bose Research Grants.</p>
<p>In the third round of grants since the program launched in 2014, four MIT faculty members — Polina Anikeeva, Martin Bazant, Nicholas Makris, and Jacquin Niles — have been selected for their innovative and unconventional proposed projects. The awardees presented their projects to MIT President L. Rafael Reif and other invited guests at a reception Monday evening.</p>
<p>The grant program is named for the late Amar Bose, a longtime member of the MIT faculty and the founder of Bose Corporation, who pursued similarly unconventional research visions. “My dad really was driven by curiosity and would do research into whatever drove his curiosity,” says his son Vanu Bose ’88, SM ’94, PhD ’99.</p>
<p>Proposals are reviewed according to the likelihood that the research could not be funded through traditional means; that the research and the researcher are intellectually adventurous; and that the project will have significant impact on the researcher. The grants offer up to $500,000 over three years.</p>
<p>“I’m impressed with both the quantity and quality of the proposals that we get each year, and I hope in the future we can fund more of them than we are today. Our goal is to attract other sources of funding to this program, as a different and better way of funding basic research,” says Vanu Bose. “We’re not short on ideas.”</p>
<p><strong>Magnetic sensing</strong></p>
<p>Anikeeva, an assistant professor of materials science and engineering, will delve into the mechanisms behind the poorly understood magnetic sensing abilities of some worms and migratory birds — and the possibility of conferring such abilities to mammals.</p>
<p>“As a materials scientist and neural engineer, I rarely get to engage in a basic biophysics project, as it is difficult to secure stable research funding for ideas outside one’s immediate area of expertise,” Anikeeva says. “Within the Bose project, together with my students, I look forward to applying our understanding of nanomagnetism to studying biophysical mechanisms of magnetosensation in several organisms.”</p>
<p>The natural world has many methods for sensing the Earth’s magnetic field, which can help organisms navigate. Some of these mechanisms are well-understood by researchers; migratory butterflies, for example, use sunlight to produce magnetism-sensitive molecules, while some bacteria contain iron particles that align along a magnetic field.</p>
<p>Other magnetism-sensing creatures remain enigmatic. Pigeons are able to navigate in a magnetic field even without light. And <em>C. elegans</em>, a type of roundworm, has been shown to use magnetic sensing to find food; hungry worms from the Northern and Southern Hemisphere burrow in opposite directions in a magnetic field — both trying to burrow “down,” deeper in the soil to find nutrients. Previous studies suggested that these worms’ magnetic sensing is genetically encoded. When researchers knocked out the gene that coded for a particular protein, the worms lost their magnetic abilities.</p>
<p>Anikeeva and her team aim to determine how exactly these birds and worms are able to sense magnetism — which genes could be involved, what those genes produce, and if it might be possible to transfer these genes and abilities to mammalian cells. The idea has intrigued Anikeeva since her days as a postdoc, when she hypothesized that magnetic fields could be used to non-invasively stimulate neurons in the brain.</p>
<p>“The concept of being able to sense magnetic fields directly … [has] persisted on the back of my mind,” she wrote in her proposal. “The Bose Grant [provides] me with a rare opportunity to fulfill my curiosity.”</p>
<p><strong>Better batteries</strong></p>
<p>Bazant, a professor of chemical engineering and mathematics, seeks to explore the theory behind room-temperature ionic liquids, which could be powerful substances for energy storage but whose properties and behavior are not well understood.</p>
<p>Ionic liquids are mixtures of charged molecules — the ions themselves form the liquid; they are not dissolved in water or another solvent — that Bazant describes as “effectively condensed plasma” with unusual properties. They are safe and stable at high voltages, making them ideal for use in batteries.</p>
<p>“Room-temperature ionic liquids hold great promise … but their physical properties are poorly understood and difficult to predict,” Bazant wrote in his proposal.</p>
<p>Bazant aims to develop the theories behind ion transport and reactions in ionic liquids, on a molecular level. Such theories would enable researchers to model and predict how different ions and additives will affect the properties of such a substance, and to create liquids well suited for various purposes.</p>
<p>"The Bose Research Grant will allow me to develop more sophisticated molecular simulations for studying the fundamental properties of ionic liquids, which could someday be used for ultrafast rechargeable batteries," Bazant says.</p>
<p>"Just as Prof. Bose supported research on the simulation of sound in buildings and achieved unexpected success, this grant may trigger advances not only in batteries, but also in supercapacitors, actuators, and green chemistry enabled by new 'fast' ionic liquids," Bazant wrote.</p>
<p><strong>Musical mysteries</strong></p>
<p>Makris, a professor of mechanical engineering, will continue a project that he and colleagues have been pursuing for seven years in their spare time out of passion and curiosity. In collaboration with Yuming Liu, a principal research scientist in mechanical engineering, Makris is exploring the fundamental physics behind masterfully crafted string instruments from the Renaissance and Baroque periods, such as Stradivarius violins.</p>
<p>“High-quality stringed instruments from violins, cellos, and viols, to guitars, lutes, and ouds are still made by master craftsmen typically using intuitive methods,” Makris wrote in his proposal. “Highly inefficient reverse engineering is required for attempted replication. Our ultimate goal is to try to help quantify the physical mechanisms leading to excellent stringed instruments so that knowledge can be passed on in a more efficient manner.”</p>
<p>Makris and Liu explained in a recent paper the physics behind air resonance in violins and how this phenomenon developed as violins evolved from their less efficient ancestors to become the acoustically powerful, lightweight instruments they are today. The researchers tested and modeled how aspects like the f-shaped holes in the instruments and the thickness of the wooden back affect the airflow and sound. But air resonance is only one piece of the violin’s spectrum of sound; now, the researchers aim to understand that entire spectrum, frequency by frequency.</p>
<p>“We hope much progress can now be made in understanding with quantitative physics how the design of some stringed instruments mysteriously evolved over centuries to enable such exceptionally high levels of performance,” Makris says. “Ultimately, this research could help to make better musical instruments available to more people and help to reveal the mechanisms by which key icons of world culture evolved."</p>
<p>"Innovative research thrives on innovative funding,” adds Makris. “We are very grateful to the Bose Research Grant for providing the nourishment that will enable our work to continue.”</p>
<p><strong>Turning an enemy into an ally</strong></p>
<p>Many would call the malaria microbe a parasite, a disease agent, or a target. But Niles, an associate professor of biological engineering, thinks there’s much more to the organism.</p>
<p>The very characteristics that make malaria a nasty disease — its ability to replicate and survive in the human bloodstream, its resistance to immune response — also make it an excellent natural platform for drug delivery, Niles explained in his proposal.</p>
<p>“Malarial organisms … represent a novel chassis for engineering microbe-based solutions for producing therapeutically valuable molecules within the circulatory system,” he wrote. His team aims to alter the genes of the malaria microbe to remove the undesirable aspects, keep the desired characteristics, and add a treatment — snip out the genes that would allow for transmission by mosquitoes, and stick in genes that would create helpful substances.</p>
<p>The human body already partners naturally with microbes — for example, “gut bacteria” in our intestinal tract help us with digestion, immunity, diabetes, and obesity — but Niles’ proposal is novel in that it suggests introducing circulating microbes in the human bloodstream and turning a parasitic enemy into a mutually beneficial ally.</p>
<p>“The human circulatory system is traditionally considered to be a sterile compartment, where the presence of microbes is strictly considered to be an indication of disease,” Niles wrote in his proposal. “By engineering these organisms to produce therapeutic molecules and simultaneously inducing clinical immunity to them, this relationship is converted into a mutualistic one.”</p>
<p>Niles notes that the idea of repurposing malaria microbes to help rather than harm may be repugnant at first, in a time when most malaria-related research seeks to eradicate the disease. But he believes that over time, the project could have a large impact.</p>
<p>“[This project] advances an unconventional, high risk-high reward strategy, that while theoretically sound, challenges several ingrained mainstream concepts,” Niles wrote. “I believe this paradigm shift will enable transformative opportunities for engineering therapeutic solutions for disease and improving human health.”</p>
Current and past recipients stand with President L. Rafael Reif and Vanu Bose, son of Amar Bose. (Left to right): Rajeev Ram, Janet Conrad, Jeffrey Grossman, Sangeeta Bhatia, Polina Anikeeva, Nicholas Makris, President Reif, Joel Voldman, Vanu Bose, Jacquin Niles, Joseph Checkelsky, Sara Seager, and Sylvia Ceyer. Faculty, awards, Awards, honors and fellowships, Research, School of Science, School of Engineering, Chemical engineering, Materials Science and Engineering, Biological engineering, Mathematics, Mechanical engineering, Grants, FundingShocking new way to get the salt out
http://news.mit.edu/2015/shockwave-process-desalination-water-1112
MIT team invents efficient shockwave-based process for desalination of water.Thu, 12 Nov 2015 00:00:00 -0500David L. Chandler | MIT News Officehttp://news.mit.edu/2015/shockwave-process-desalination-water-1112<p>As the availability of clean, potable water becomes an increasingly urgent issue in many parts of the world, researchers are searching for new ways to treat salty, brackish or contaminated water to make it usable. Now a team at MIT has come up with an innovative approach that, unlike most traditional desalination systems, does not separate ions or water molecules with filters, which can become clogged, or boiling, which consumes great amounts of energy.</p>
<p>Instead, the system uses an electrically driven shockwave within a stream of flowing water, which pushes salty water to one side of the flow and fresh water to the other, allowing easy separation of the two streams. The new approach is described in the journal <em>Environmental Science and Technology Letters</em>, in a paper by professor of chemical engineering and mathematics Martin Bazant, graduate student Sven Schlumpberger, undergraduate Nancy Lu, and former postdoc Matthew Suss.</p>
<p>This approach is “a fundamentally new and different separation system,” Bazant says. And unlike most other approaches to desalination or water purification, he adds, this one performs a “membraneless separation” of ions and particles.</p>
<p>Membranes in traditional desalination systems, such as those that use reverse osmosis or electrodialysis, are “selective barriers,” Bazant explains: They allow molecules of water to pass through, but block the larger sodium and chlorine atoms of salt. Compared to conventional electrodialysis, “This process looks similar, but it’s fundamentally different,” he says.</p>
<p>In the new process, called shock electrodialysis, water flows through a porous material —in this case, made of tiny glass particles, called a frit — with membranes or electrodes sandwiching the porous material on each side. When an electric current flows through the system, the salty water divides into regions where the salt concentration is either depleted or enriched. When that current is increased to a certain point, it generates a shockwave between these two zones, sharply dividing the streams and allowing the fresh and salty regions to be separated by a simple physical barrier at the center of the flow.</p>
<p>“It generates a very strong gradient,” Bazant says.</p>
<p>Even though the system can use membranes on each side of the porous material, Bazant explains, the water flows across those membranes, not through them. That means they are not as vulnerable to fouling — a buildup of filtered material — or to degradation due to water pressure, as happens with conventional membrane-based desalination, including conventional electrodialysis. “The salt doesn’t have to push through something,” Bazant says. The charged salt particles, or ions, “just move to one side,” he says.</p>
<p>The underlying phenomenon of generating a shockwave of salt concentration was discovered a few years ago by the group of Juan Santiago at Stanford University. But that finding, which involved experiments with a tiny microfluidic device and no flowing water, was not used to remove salt from the water, says Bazant, who is currently on sabbatical at Stanford.</p>
<p>The new system, by contrast, is a continuous process, using water flowing through cheap porous media, that should be relatively easy to scale up for desalination or water purification. “The breakthrough here is the engineering [of a practical system],” Bazant says.</p>
<p>One possible application would be in cleaning the vast amounts of wastewater generated by hydraulic fracturing, or fracking. This contaminated water tends to be salty, sometimes with trace amounts of toxic ions, so finding a practical and inexpensive way of cleaning it would be highly desirable. This system not only removes salt, but also a wide variety of other contaminants — and because of the electrical current passing through, it may also sterilize the stream. “The electric fields are pretty high, so we may be able to kill the bacteria,” Schlumpberger says.</p>
<p>The research produced both a laboratory demonstration of the process in action and a theoretical analysis that explains why the process works, Bazant says. The next step is to design a scaled-up system that could go through practical testing.</p>
<p>Initially at least, this process would not be competitive with methods such as reverse osmosis for large-scale seawater desalination. But it could find other uses in the cleanup of contaminated water, Schlumpberger says.</p>
<p>Unlike some other approaches to desalination, he adds, this one requires little infrastructure, so it might be useful for portable systems for use in remote locations, or for emergencies where water supplies are disrupted by storms or earthquakes.</p>
<p>Maarten Biesheuvel, a principal scientist at the Netherlands Water Technology Institute who was not involved in this research, says the work “is of very high significance to the field of water desalination. It opens up a whole range of new possibilities for water desalination, both for seawater and brackish water resources, such as groundwater.”</p>
<p>Biesheuvel adds that this team “shows a radically new design where within one and the same channel ions are separated between different regions. … I expect that this discovery will become a big ‘hit’ in the academic field. … It will be interesting to see whether the upscaling of this technology, from a single cell to a stack of thousands of cells, can be achieved without undue problems.”</p>
<p>The research was supported by the MIT Energy Initiative, Weatherford International, the USA-Israel Binational Science Foundation, and the SUTD-MIT Graduate Fellows Program.</p>
Researchers say the new desalination method could be useful for cleaning the contaminated water generated by hydraulic fracturing, or fracking. Shown here is a holding pit for fracking water.
Research, Desalination, School of Engineering, School of Science, Chemical engineering, Mathematics, WaterEdward Boyden wins 2016 Breakthrough Prize in Life Sciences
http://news.mit.edu/2015/edward-boyden-2016-breakthrough-prize-life-sciences-1109
MIT physicists share prize in fundamental physics; Larry Guth and Liang Fu win New Horizons Prizes. Mon, 09 Nov 2015 14:30:00 -0500News Officehttp://news.mit.edu/2015/edward-boyden-2016-breakthrough-prize-life-sciences-1109<p>MIT researchers took home several awards last night at the 2016 <a href="https://breakthroughprize.org/">Breakthrough Prize</a> ceremony at NASA’s Ames Research Center in Mountain View, California.</p>
<p>Edward Boyden, an associate professor of media arts and sciences, biological engineering, and brain and cognitive sciences, was one of five scientists honored with the Breakthrough Prize in Life Sciences, given for “transformative advances toward understanding living systems and extending human life.” He will receive $3 million for the award.</p>
<p>MIT physicists also contributed to a project that won the Breakthrough Prize in Fundamental Physics. That prize went to five experiments investigating the oscillation of subatomic particles known as neutrinos. More than 1,300 contributing physicists will share in the recognition for their work, according to the award announcement. Those physicists include MIT associate professor of physics Joseph Formaggio and his team, as well as MIT assistant professor of physics Lindley Winslow.</p>
<p>Larry Guth, an MIT professor of mathematics, was honored with the New Horizons in Mathematics Prize, which is given to promising junior researchers who have already produced important work in mathematics. Liang Fu, an assistant professor of physics, was honored with the New Horizons in Physics Prize, which is awarded to promising junior researchers who have already produced important work in fundamental physics.</p>
<p>“By challenging conventional thinking and expanding knowledge over the long term, scientists can solve the biggest problems of our time,” said Mark Zuckerberg, chairman and CEO of Facebook, and one of the prizes’ founders. “The Breakthrough Prize honors achievements in science and math so we can encourage more pioneering research and celebrate scientists as the heroes they truly are.”</p>
<p><strong>Optogenetics</strong></p>
<p>Boyden was honored for the development and implementation of <a href="https://www.youtube.com/watch?v=Nb07TLkJ3Ww">optogenetics</a>, a technique in which scientists can control neurons by shining light on them. Karl Deisseroth, a Stanford University professor who worked with Boyden to pioneer the technique, was also honored with one of the life sciences prizes.</p>
<p>Optogenetics relies on light-sensitive proteins, originally isolated from bacteria and algae. About 10 years ago, Boyden and Deisseroth began engineering neurons to express these proteins, allowing them to selectively stimulate or silence them with pulses of light. More recently, Boyden has developed additional proteins that are even more sensitive to light and can respond to different colors.</p>
<p>Scientists around the world have used optogenetics to reveal the brain circuitry underlying normal neural function as well as neurological disorders such as autism, obsessive-compulsive disorder, and depression.</p>
<p>Boyden is a member of the MIT Media Lab and MIT’s McGovern Institute for Brain Research.</p>
<p><strong>Neutrino oscillations</strong></p>
<p>The Breakthrough Prize in Fundamental Physics was awarded to five research projects investigating the nature of neutrinos: Daya Bay (China); KamLAND (Japan); K2K/T2K (Japan); Sudbury Neutrino Observatory (Canada); and Super-Kamiokande (Japan). Researchers with these experiments were recognized “for the fundamental discovery of neutrino oscillations, revealing a new frontier beyond, and possibly far beyond, the standard model of particle physics.”</p>
<p>Formaggio and his team at MIT have been collaborating on the Sudbury Neutrino Observatory (SNO) project since 2005. Research at the observatory, 2 kilometers underground in a mine near Sudbury, Ontario, demonstrated that neutrinos change their type — or “flavor” — on their way to Earth from the sun. </p>
<p>Winslow has been a collaborator on KamLAND, located in a mine in Japan, since 2001. Using antineutrinos from nuclear reactors, this experiment demonstrated that the change in flavor was energy-dependent. The combination of these results solved the solar neutrino puzzle and proved that neutrinos have mass. </p>
<p>The MIT SNO group has participated heavily on the analysis of neutrino data, particularly during that experiment’s final measurement phase. The MIT KamLAND group is involved with the next phase, KamLAND-Zen, which is searching for a rare nuclear process that if observed, would make neutrinos their own antiparticles.</p>
<p><strong>Reaching new horizons</strong></p>
<p>Guth, who will receive a $100,000 prize, was honored for his “ingenious and surprising solutions to long standing open problems in symplectic geometry, Riemannian geometry, harmonic analysis, and combinatorial geometry.”</p>
<p>Guth’s work at MIT focuses on combinatorics, or the study of discrete structures, and how sets of lines intersect each other in space. He also works in the area of harmonic analysis, studying how sound waves interact with each other.</p>
<p>Guth’s father, MIT physicist Alan Guth, won the inaugural Breakthrough Prize in Fundamental Physics in 2015.</p>
<p>Fu will share a New Horizons in Physics Prize with two other researchers: B. Andrei Bernevig of Princeton University and Xiao-Liang Qi of Stanford University. The physicists were honored for their “outstanding contributions to condensed matter physics, especially involving the use of topology to understand new states of matter.”</p>
<p>Fu works on theories of topological insulators — a new class of materials whose surfaces can freely conduct electrons even though their interiors are electrical insulators — and topological superconductors. Such materials may provide insight into quantum physics and have possible applications in creating transistors based on the spin of particles rather than their charge.</p>
<p>Yesterday’s prize ceremony was hosted by producer/actor/director Seth MacFarlane; awards were presented by the prize sponsors and by celebrities including actors Russell Crowe, Hilary Swank, and Lily Collins. The Breakthrough Prizes were founded by Sergey Brin and Anne Wojcicki, Jack Ma and Cathy Zhang, Yuri and Julia Milner, and Mark Zuckerberg and Priscilla Chan.</p>
<p>“Breakthrough Prize laureates are making fundamental discoveries about the universe, life, and the mind,” Yuri Milner said. “These fields of investigation are advancing at an exponential pace, yet the biggest questions remain to be answered.”</p>
(Left to right) Edward Boyden, Larry Guth, and Liang FuAwards, honors and fellowships, Faculty, McGovern Institute, Media Lab, Brain and cognitive sciences, Biological engineering, Mathematics, Physics, School of Science, School of Engineering, School of Architecture and PlanningFaster optimization
http://news.mit.edu/2015/faster-optimization-algorithm-1023
New general-purpose optimization algorithm promises order-of-magnitude speedups on some problems.Fri, 23 Oct 2015 00:00:00 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2015/faster-optimization-algorithm-1023<p>Optimization problems are everywhere in engineering: Balancing design tradeoffs is an optimization problem, as are scheduling and logistical planning. The theory — and sometimes the <a href="http://news.mit.edu/2015/robotics-competition-algorithms-0611">implementation</a> — of control systems relies heavily on optimization, and so does machine learning, which has been the basis of most recent advances in artificial intelligence.</p>
<p>This week, at the IEEE Symposium on Foundations of Computer Science, a trio of present and past MIT graduate students won a best-student-paper award for a new “cutting-plane” algorithm, a general-purpose algorithm for solving optimization problems. The algorithm improves on the running time of its most efficient predecessor, and the researchers offer some reason to think that they may have reached the theoretical limit.</p>
<p>But they also present a new method for applying their general algorithm to specific problems, which yields huge efficiency gains — several orders of magnitude.</p>
<p>“What we are trying to do is revive people’s interest in the general problem the algorithm solves,” says Yin-Tat Lee, an MIT graduate student in mathematics and one of the paper’s co-authors. “Previously, people needed to devise different algorithms for each problem, and then they needed to optimize them for a long time. Now we are saying, if for many problems, you have one algorithm, then, in practice, we can try to optimize over one algorithm instead of many algorithms, and we may have a better chance to get faster algorithms for many problems.”</p>
<p>Lee is joined on the paper by Aaron Sidford, who was an MIT graduate student in electrical engineering and computer science when the work was done but is now at Microsoft Research New England, and by Sam Wong, who earned bachelor’s and master’s degrees in math and electrical engineering and computer science at MIT before moving to the University of California at Berkeley for his PhD.</p>
<p><strong>Inner circle</strong></p>
<p>Optimization problems are generally framed as trying to find the minimum value of a mathematical function, called a “cost function.” In car design, for example, the cost function might impose penalties for weight and drag but reward legroom and visibility; in an algorithm for object detection, the cost function would reward correct classification of various objects and penalize false positives.</p>
<p>At a very general level, finding the minimum of a cost function can be described as trying to find a small cluster of values amid a much larger set of possibilities. Suppose that the total range of possible values for a cost function is represented by the interior of a circle. In a standard optimization problem, the values clustered around the minimum value would then be represented by a much smaller circle inside of the first one. But you don’t know where it is.</p>
<p>Now pick a point at random inside the bigger circle. In standard optimization problems, it’s generally possible to determine whether that point lies within the smaller circle. If it doesn’t, it’s also possible to draw a line that falls between it and the smaller circle.</p>
<p>Drawing that line cuts off a chunk of the circle, eliminating a range of possibilities. With each new random point you pick, you chop off another section of the circle, until you converge on the solution.</p>
<p>If you represent the range of possibilities as a sphere rather than a circle, then you use a plane, rather than a line, to cut some of them off. Hence the name for the technique: the cutting-plane method.</p>
<p>In most real optimization problems, you need a higher-dimensional object than either a circle or a sphere: You need a hypersphere, which you cut with a hyperplane. But the principle remains the same.</p>
<p><strong>A matter of time</strong></p>
<p>Theoretical computer scientists measure algorithms’ running times not in seconds or hours, but in the number of operations required, relative to the number of elements being manipulated. With cutting-plane methods, the number of elements is the number of variables in the cost function — the weight of the car, the cost of its materials, drag, legroom, and so on. That’s also the dimension of the hypersphere.</p>
<p>With the best general-purpose cutting-plane method, the time required to select each new point to test was proportional to the number of elements raised to the power 3.373. Sidford, Lee, and Wong get that down to 3.</p>
<p>But they also describe a new way to adapt cutting-plane methods to particular types of optimization problems, with names like submodular minimization, submodular flow, matroid intersection, and semidefinite programming. And in many of those cases, they report dramatic improvements in efficiency, from running times that scale with the fifth or sixth power of the number of variables (n<sup>5</sup> or n<sup>6</sup>, in computer science parlance) down to the second or third power (n<sup>2</sup> or n<sup>3</sup>).</p>
<p>“This is indeed an astonishing paper,” says Satoru Iwata, a professor of mathematical informatics at the University of Tokyo, who has published widely on the problem of submodular minimization. “For this problem,” he says, “the running time bounds derived with the aid of discrete geometry and combinatorial techniques are by far better than what I could imagine.”</p>
"Cutting plane" methods converge on the optimal values of a mathematical function by repeatedly cutting out regions of a much larger set of possibilities (gold sphere).Research, School of Engineering, School of Science, Algorithms, Computer science and technology, Mathematics, Computer Science and Artificial Intelligence Laboratory (CSAIL), Electrical engineering and computer science (EECS)David Benney, emeritus professor of mathematics, dies at 85
http://news.mit.edu/2015/david-benney-mit-applied-mathematician-dies-1016
World-renowned applied mathematician's 50-year career at MIT included service as Department of Mathematics head from 1989 to 1999.Fri, 16 Oct 2015 12:20:01 -0400Department of Mathematicshttp://news.mit.edu/2015/david-benney-mit-applied-mathematician-dies-1016
<p>David J. Benney, professor emeritus of applied mathematics at MIT and former head of the Department of Mathematics, died on Oct. 9 after a period of declining health. He was 85.</p>
<p>Benney joined the MIT mathematics faculty in 1960 as assistant professor. He received a PhD in applied mathematics from MIT in 1959, studying under Chai-Chiao Lin, and continued at MIT as an instructor in 1959-60. He was promoted to full professor in 1966, and retired from MIT in 2010.</p>
<p>Benney chaired the Applied Mathematics Committee from 1983 to 85. He served as department head for two terms between 1989-99, a period of major transition for the department and MIT. Benney set the pace for future departmental administrations through major fundraising, building innovation, and furthering the department’s cross-disciplinary culture. He expanded the visiting professorship program and hosted several first-rate visitors. He oversaw the appointment of many leading scholars to the faculty, thereby establishing the current strength of the department.</p>
<p>David Benney’s research was highly original; as such, he made pioneering contributions to applied mathematics. He was at the leading edge of a paradigm shift in thinking about nonlinear wave systems in fluid dynamics. He not only rationalized important physical phenomena, but derived equations to describe them that became relevant in a wide variety of contexts, including aerodynamics, meteorology, oceanography, atmospheric sciences, and optics.</p>
<p>Benney’s principal research contributions lie in the mathematical analysis of nonlinear waves, hydrodynamic stability, and transitions to turbulence. Beginning with his PhD under the direction of C.C. Lin in the 1950s, Benney and early collaborators showed that nonlinear wave interactions were fundamental to the study of hydrodynamic stability, and could lead to the emergence of turbulent bursts, as were later observed in experiments done at the National Bureau of Standards. </p>
<p>Benney did pioneering work clarifying how nonlinearity could affect the stability of flows including shear flows over plates. This was a major advance in the field and led to many important developments in the theory of turbulence. He continued his studies of hydrodynamical stability and transition through his mentoring of numerous doctoral students and postdoctoral associates.</p>
<p>His research on the dynamics of nonlinear waves had enormous impact in multiple fields. In his early work in 1962 describing nonlinear wave interactions in water waves, Benney developed key mathematical tools that were subsequently used extensively by the applied mathematics community. In 1964, he and his graduate student, J. Luke, derived an equation governing three dimensional weakly nonlinear shallow water waves. This equation, known as the “Benney-Luke Equation,” led to considerable research and applies in a variety of physical settings, including long wave interactions on flat beaches and long distance tsunami propagation. His further work on long waves was seminal: He showed how to find the governing equations in general circumstances. His related research on wave propagation in thin films has been used widely in many technological applications such as film-based photography and coating of materials. His research in the 1970s on large-amplitude long waves led him to formulate a novel system of equations, the so-called “Benney system,” that has since been the subject of many mathematical investigations.</p>
<p>Benney’s research was often ahead of his time. In 1967, with his first PhD student, A. Newell, Benney showed that a particular equation (known as the nonlinear Schrödinger equation) arises universally in diverse applications in nonlinear dispersive waves. Subsequent researchers found that this equation arises in the mathematical description of water waves, plasma physics and intense light waves. He soon followed with important work on three-dimensional modulated waves in water. With his student G. Roskes, he derived a system of equations, known as the "Benney-Roskes" equations, which has been widely used. Shortly thereafter, with his student M. Ablowitz, he formulated a novel class of quasi-periodic modulated wave trains. Years later, this too was found to arise in various physical systems, including fluid dynamics, optics and Bose-Einstein condensates.</p>
<p>Benney was a dedicated teacher and mentor who left an extraordinary legacy. He had a remarkable ability to work effectively with PhD students and he mentored 18 PhDs, producing 158 academic descendants. </p>
<p>Benney was beloved of colleagues who knew him well and worked with him closely. One of his colleagues, (and a former student) says, “Dave was a modest man who had little to be modest about. With his gentle, self-effacing manner and humor, he tended to deflect any superlatives and accolades aimed in his direction. But in truth, he was a first rate leader: generous to all, regardless of rank, he had a strong moral compass, a principled view of life and a backbone of steel when it came to doing the right thing.”</p>
<p>A conference was held in 2000 in honor of his 70th birthday. An account of his many contributions can be found in "Research Contributions of David J. Benney," by M. Ablowitz, T. Akylas and C.C. Lin, in <em>Studies in Applied Mathematics</em> (Vol 108, 2002, p.1-6). That issue also contains a number of articles written by his former students and colleagues in his honor.</p>
<p>Benney served for 46 years (1968-2013) as managing editor of <em>Studies in Applied Mathematics. </em>Under his long tenure, he steered the journal to prominence, making it a leading journal in physical applied mathematics.</p>
<p>With Harvey Greenspan, he co-authored the widely-used text, "Calculus: An Introduction to Applied Mathematics," published in 1973 by McGraw Hill (later republished by Breukelin Press in 1997).</p>
<p>David John Benney, was born in Wellington, New Zealand, on April 8, 1930. He received his BS in mathematics (with first class honors) from Victoria University in Wellington, New Zealand, in 1950, followed by an MS in 1951. He studied at Cambridge University from 1952 to 1954, receiving a BA in mathematics, again with first-class honors. He returned to New Zealand as a lecturer at Canterbury University College (1955-57), before entering the doctoral program at MIT in applied mathematics.</p>
<p>David Benney is survived by his wife of 56 years, Elizabeth Matthews Benney; by his three children, Richard Benney of Stow, Vermont; Paul Benney of Bloomfield, Connecticut; and Antonia Benney of Longmeadow, Massachusetts; and by two grandsons, Luke and Jon.</p>
<p>A celebration of David Benney’s life will be held for family, friends and colleagues at his home on Oct. 18.</p>
Professor emeritus David Benney served two terms as head of the Department of Mathematics at MIT.Mathematics, Obituaries, School of Science, FacultyNew to campus
http://news.mit.edu/2015/meet-class-of-2019-1002
Members of the Class of 2019 possess ample talent and determination. Fri, 02 Oct 2015 00:00:00 -0400Jennifer Chu | MIT News Officehttp://news.mit.edu/2015/meet-class-of-2019-1002<p>With the first few weeks of classes now under their belts, first-year students are settling into the busy, challenging, and often exciting new life of the MIT student.</p>
<p>In these early days, MIT freshmen will no doubt be taking in new experiences at a breathless clip — an initiation that many at MIT equate with “drinking from the fire hose.”</p>
<p>But for first-year students like Abishkar Chhetri, the flood of education may feel more like a welcome rain after a long drought. Chhetri — one of 1,109 members of the Class of 2019 — says his admittance to MIT had a “one in a million chance of happening.”</p>
<p>Chhetri was born in a refugee camp in eastern Nepal, where he lived for the first seven years of his life, with little opportunity for a quality education. As he wrote in his application to MIT, “I opened my eyes to a world that promised me no future.”</p>
<p>The camp housed people in bamboo and straw huts, and Chhetri remembers attending the camp’s one school, where attendance was mandatory, although resources — both physical and mental — were meager.</p>
<p>“There were no desks or chairs — you sat on the floor,” Chhetri remembers. “There weren’t a lot of rooms, and it was really crowded, so sometimes you felt very suffocated.”</p>
<p>His parents, intent on giving Chhetri and his younger sister a better education, found jobs in Nepal’s capital, Katmandu, where they eventually moved the family when Chhetri was 7 years old. The improved schooling there, with more resources and qualified teachers, was “a new world for me — a place where I can be curious, and finally study without worrying about what I’m going to eat,” Chhetri says.</p>
<p>But after two years, the family’s dwindling finances forced them back to the refugee camp. Soon after, they learned of, and applied to, a resettlement program in the United States, which ultimately accepted them. In 2010, Chhetri and his family arrived in Atlanta with little money, and even less understanding of English.</p>
<p>Chhetri enrolled in an international baccalaureate school in suburban Decatur — and while he struggled with learning the language, he found he excelled at math.</p>
<p>“I didn’t have very good language skills, so learning social studies wasn’t very encouraging,” Chhetri recalls. “But math is a language in itself. So my ability in mathematics kept me going.”</p>
<p>To improve his English, he looked to YouTube, watching hours of documentaries and educational videos on a computer donated to his family. Through his online meanderings, he came across MIT’s OpenCourseWare, where he eagerly absorbed lectures on physics and math.</p>
<p>“I wasn’t sure I could attend a university like this, but I thought: Unrealistic things happen,” Chhetri says.</p>
<p>Today, as an MIT freshman, Chhetri is the first member of his family to attend a four-year college.</p>
<p>“Having a goal that means a lot to you, and doing everything possible to chase after it, I think that’s what makes life worthwhile, no matter if you succeed or not,” Chhetri says.</p>
<p><strong>Freshmen by the numbers</strong></p>
<p>Chhetri was one of a pool of 18,306 applicants to MIT, of whom just 1,519 were admitted to the Class of 2019 — an acceptance rate of 8.3 percent. Of those, 1,109 students have enrolled at the Institute, for a yield of 73 percent. The freshman class is 53 percent male and 47 percent female, and ethnically diverse: 32 percent self-identify as Asian-American; 10 percent as black or African-American; 14 percent as Hispanic or Latino; 2 percent as American Indian or Alaskan native; and 51 percent as white or Caucasian. Overall, 10 percent of the freshman class is of international citizenry, representing 69 countries.</p>
<p>MIT’s first-year students graduated from 835 different high schools, 65 percent of which were public; 14 percent independent; 9 percent religious; and 10 percent foreign. One percent of the incoming students were homeschooled.</p>
<p><strong>Life on the ice</strong></p>
<p>For incoming students, the MIT experience can be a healthy mix of competition and fun — a combination that Zoe Gong knows well. Growing up in Ottawa, Ontario, Gong dove into the world of competitive figure skating at an early age. When she was 4, her mother took her to a local rink, where she quickly took to the ice.</p>
<p>Soon after, Gong took up skating lessons, entering a number of local competitions. As she honed her skills, and began to qualify for and place in higher-level competitions, she found skating gradually morphed from casual fun to a serious sport.</p>
<p>She eventually set her sights on the Canadian National Figure Skating Championships, and aimed to qualify and compete in the novice category. The road to the finals would include several rounds of stiff competition, and Gong’s parents gave her the best chance at making it through: At 13, they moved to Colorado Springs, Colorado, where she trained 30 hours per week at the U.S. Olympic Training Site for the next three years.</p>
<p>Gong says that for much of her skating career, nerves had little effect on her performance. But at the start of the 2013 competition season, something felt off.</p>
<p>“I was having a lot of trouble with jumps, and would get really scared and anxious and nervous, and couldn’t make myself commit, and I would fall a lot,” Gong says. “It really got to me mentally.”</p>
<p>She decided to call it quits, and stopped training for several months. What got her back on the ice was the support of friends — fellow competitors in the skating community. With their backing, Gong started training again, slowly working her way up through the rankings, and eventually, to the finals. All her hard work paid off, as Gong won gold, taking up the 2013 national champion title.</p>
<p>“That year definitely taught me how to fall down a lot, very painfully, and get back up every time and go around again and do the exact same thing,” Gong says.</p>
<p>She credits part of her success to her skating “family” — coaches and fellow competitors, who taught her more than the sport itself. Through this community, Gong became active in raising awareness of LGBTQ issues, and organized fundraisers at her high school to support charities and foundations.</p>
<p>“The figure-skating community is really open, and I was lucky to have grown up around really accepting and welcoming and queer-friendly people,” Gong says. “I think it’s really important to help people who are less fortunate, and grew up in less accepting and tolerant communities.”</p>
<p>At MIT, Gong hopes to “give a little back to the sport” by perhaps coaching through the Figure Skating Club. As for what to study, she’s considering computer science or mechanical engineering, although she’s eager to explore her options.</p>
<p>“I want to keep an open mind and try as many things as possible to find something I’m really passionate about, and that I’d like to work on forever,” Gong says.</p>
<p><strong>The universal language</strong></p>
<p>For Michael Hartman, attending MIT — or any school, for that matter — is an entirely new experience. Hartman, who hails from Greenville, South Carolina, was homeschooled for his entire education by his mother, a registered nurse with a bachelor’s degree in computer science. His father was a manager at the chemical company BASF, a job that would move the family several times within Louisiana and South Carolina. Homeschooling, then, was a dependable constant for Hartman and his brother. It also gave them flexibility and spontaneity in choosing what to study.</p>
<p>Hartman recalls one particular school day, when he was about 5 years old. His mother was driving the brothers home from an outing when she declared that the boys would learn to play instruments, and pulled the car into a local music store. Inside, the owner brought out a viola and started to play.</p>
<p>“I was just captivated by how good it sounded, and I was going to say, ‘I want to play the viola’ — but I talk very slow, so my brother got it out before I did,” Hartman says. “I didn’t want to make it look like I was just copying him, so I said, ‘I’ll take the big one.’”</p>
<p>Hartman now describes playing cello as a way to “tell stories that have no words … told in the universal language of music.” He has gone on to win numerous awards in solo and orchestral performance; last January, he performed as a soloist with the Young Artist Orchestra in Greenville.</p>
<p>In high school, Hartman and his brother founded the Brothers Hartman String Duet, and performed at various functions around town, even appearing on a local television program showcasing young talent. The group’s highest-profile gig came about by happenstance.</p>
<p>“My dad was on a plane going somewhere for a business trip, and he said to the person sitting beside him, ‘You look exactly like Wynton Marsalis,’” Hartman says.</p>
<p>The man turned out to be Marsalis’ brother, Delfeayo, a noted jazz trombonist. Hartman’s father told Marsalis about his sons, who in turn asked for a recording. In 2010, the brothers were invited to play at a jazz festival with Marsalis and the New Orleans Philharmonic.</p>
<p>At MIT, Hartman hopes to join the MIT Symphony Orchestra, and to continue to take private lessons. But he’s most excited about the hands-on prospects of mechanical engineering, which he got a taste of through his senior project — disassembling and then reassembling the engine of the family’s lawnmower.</p>
<p>Hartman has also long held a fascination with high-performance cars, and has ambitious goals of producing a line of his own some day.</p>
<p>“I want to be an engineer because I like to build stuff,” Hartman says. “But I also figured out what I really wanted to do is make my own car brand, like Ferrari, Lamborghini, Hartman. It seems impossible, but there are people who do it, and if it’s not impossible, that’s good enough for me.”</p>
<p><strong>Standing for STEM</strong></p>
<p>A similar determination has driven Riana Hoagland. Raised in Olympia, Washington, by her mother, a math teacher, and her father, a computer science teacher, Hoagland grew up with an ingrained curiosity for all things related to science and technology. In school, she excelled at math and science, and developed an early interest in computer science.</p>
<p>It wasn’t until 11th grade that Hoagland looked around her physics class and noticed only a handful of other girls in the room. The same went for her calculus class.</p>
<p>“I never had a problem being interested in these subjects, but some of my best friends weren’t as good, and always felt they weren’t really supposed to be an engineer — that’s a guy thing,” Hoagland says.</p>
<p>She herself felt the stereotype when looking for clubs to join. “The computer science, math, and robotics clubs were just all guys, and it was a little intimidating,” Hoagland says.</p>
<p>To reverse the stereotype, she and 30 other girls at the school, along with their math teacher, started the dotDiva Club, taking a page from the national organization by the same name, which works to support women in science, technology, engineering, and mathematics (STEM) fields. Hoagland served as president of the club for its first two years, during which the club offered computer programming lessons using Java, Lego Mindstorm robots, and RobotC programming. Hoagland also organized a schoolwide “Hour of Code,” part of a worldwide effort to teach students computer programming through hourlong tutorials.</p>
<p>Hoagland doesn’t plan to become a computer scientist, although she says familiarity with computers is becoming an essential skill in many fields.</p>
<p>“Computer science is now super-important,” Hoagland says. “I’m going to go into biological engineering, and you need computer skills to code all your data. Even if you’re not going to be a computer scientist, you still need to know what you’re doing.”</p>
<p>Hoagland already has quite a bit of experience in both computer science and biology. For the last two years, she’s volunteered in several biology and neuroengineering labs, most recently working as an assistant with a research group in Olympia where scientists are investigating the neurological basis for behaviors during early development. Hoagland has helped analyze videos of premature babies, taking down instances when infants touch themselves, and matching the data up with pre-recorded heart-rate responses. The scientists hope the data will elucidate ways in which babies first develop self-awareness.</p>
<p>At MIT, Hoagland plans to study bioengineering, with the ultimate goal of earning a PhD and eventually running her own lab to develop medical innovations. She also wants to inspire other girls to do the same, and hopes to participate in campus outreach programs to recruit elementary and middle school girls to STEM fields.</p>
<p>“It’s important to get them into it at an early age to make sure they don’t get a bad representation of STEM in their minds,” Hoagland says. “I’d really like there to be more girls. I don’t want there to be any stereotypes of me like, ‘She’s a girl.’ Yeah, so?”</p>
Members of the MIT Class of 2019: Riana Hoagland, Zoe Gong, Michael Hartman, Abishkar ChhetriStudents, Undergraduate, Admissions, Bioengineering and biotechnology, Computer science and technology, Education, teaching, academics, Music, Mathematics, online learning, Physics, Diversity, Women in STEM, Volunteering, outreach, public service, ArtsAlexei Borodin receives the 2015 Henri Poincaré Prize
http://news.mit.edu/2015/alexei-borodin-receives-henri-poincar%C3%A9-prize-0928
Mathematics professor honored for contributions to mathematical physics that lay the groundwork for new developments in the field.Mon, 28 Sep 2015 14:24:01 -0400Helen Knight | MIT News correspondenthttp://news.mit.edu/2015/alexei-borodin-receives-henri-poincar%C3%A9-prize-0928<p>Alexei Borodin, professor of mathematics at MIT, has been awarded the prestigious 2015 Henri Poincaré Prize by the International Association of Mathematical Physics.</p>
<p>The award’s citation reads, “Alexei Borodin is honored for his seminal contributions to the theory of big groups, to determinantal processes and most notably to the elucidation of Macdonald processes, which have important applications to the statistical physics of directed polymers, tiling models and random surfaces.”</p>
<p>Borodin’s research lies at the interface of group representation theory, the study of symmetries, and probability theory. Using sophisticated mathematical tools, he is able to show that many previously intractable probabilistic systems are in fact integrable — or exactly solvable. In this way he is able to extract detailed information from what appear to be random structures. “The results often predict similar behavior for much broader varieties of probabilistic objects,” Borodin says. “This is much like the bell-shaped curve that arises from flipping a coin that ends up being the universal limiting object in one-dimensional probability.”</p>
<p>The Henri Poincaré Prize is one of the most distinguished awards in mathematical physics, awarded every three years at the International Mathematical Physics Congress.</p>
<p>Prior recipients of the prize include a number of Fields Medalists, MacArthur Foundation Fellows, and Heineman Prize winners, including notable scholars such as Freeman Dyson, Maxim Kontsevich and Edward Witten, according to Tomasz Mrowka, head of the Department of Mathematics at MIT. “We congratulate Alexei on his award,” Mrowka says.</p>
<p>Borodin was also awarded the 2015 Line and Michel Loève International Prize in Probability. A graduate of Moscow State University, he received a PhD from the University of Pennsylvania in 2001, studying under Alexandre Kirilov. In 2003 Borodin was appointed professor of mathematics at Caltech, where he remained until 2010. During this time he was awarded the Prize of the Moscow Mathematical Society and the Prize of the European Mathematical Society. He joined the MIT mathematics faculty in 2010.</p>
<p>The Henri Poincaré Prize, which is sponsored by the Daniel Iagolnitzer Foundation, was created in 1997. It is awarded every three years to several individuals, each of whom has made a contribution to mathematical physics that lays the groundwork for new developments in the field.</p>
Alexei BorodinFaculty, Awards, honors and fellowships, Mathematics, School of ScienceFive professors join the School of Science this fall
http://news.mit.edu/2015/five-professors-join-school-science-0925
Fri, 25 Sep 2015 17:08:01 -0400School of Sciencehttp://news.mit.edu/2015/five-professors-join-school-science-0925<p>The School of Science welcomes five new professors in the departments of Earth, Atmospheric and Planetary Sciences; Mathematics; and Physics. Their research ranges from exploring problems in pure math to the evolution of animal life on Earth to the evolution of galaxies.</p>
<p><strong>Kristin Bergmann</strong>, assistant professor in the Department of Earth, Atmospheric and Planetary Sciences, works to reconstruct the record of environmental change from observations of sedimentary rocks from latest Precambrian to Ordovician time. To date, she has worked on carbonate sedimentary rocks in order to better understand how the chemistry and climate of the oceans and atmosphere have affected the evolution of animal life over this time. She received a BA in geology and environmental studies from Carleton College in 2004 and completed her PhD at Caltech in 2013 under the direction of professors John Grotzinger, Woody Fischer, and John Eiler. Before joining the MIT faculty, she was a junior fellow with the Harvard Society of Fellows, working with Professor Andy Knoll.</p>
<p><strong>Davesh Maulik</strong>, professor of mathematics, completed his doctoral work at Princeton University in 2007, studying under Rahul Pandharipande. That year, he received a five-year research fellowship from the Clay Mathematics Institute, which he took in postdoctoral appointments at Columbia University and at MIT. In 2011, he joined the faculty at Columbia as an associate professor with tenure. In 2009, he received the Compositio Mathematica Prize with co-authors for an outstanding research publication. He was an invited speaker at the International Congress of Mathematicians in Korea in 2014.</p>
<p>Maulik works in algebraic geometry. His interests concern moduli spaces of geometric objects — for example, algebraic curves or sheaves — and various questions regarding their structure. In many cases, these require developing and exploiting connections with related fields such as mathematical physics, symplectic geometry, and representation theory. </p>
<p><strong>Michael McDonald </strong>joins the Department of Physics and the Kavli Institute for Astrophysics and Space Research as an assistant professor. His research focuses on the most massive gravitationally-bound objects in the universe: clusters of galaxies. In particular, he is attempting to understand the life cycle of gas, stars, and galaxies in these rich environments, and how highly energetic processes such as supernovae and jets from supermassive black holes can influence the evolution of these systems. This research makes extensive use of both ground- and space-based telescopes at nearly all wavelengths, including (but not limited to) the Magellan and ALMA observatories in Chile, the South Pole Telescope in Antarctica, and the space-based Chandra and Hubble telescopes. Aside from research, McDonald has been involved in the development of the Maryland-Magellan Tunable Filter on the Baade telescope at Magellan and is a member of the Science Working Group for the European Athena X-ray telescope, scheduled to launch in the late 2020s.</p>
<p>McDonald received a bachelor’s degree in physics in 2005 and an MS in 2007, both from Queen’s University in Canada. He completed his doctoral work at the University of Maryland in 2011, working with Professor Sylvain Veilleux on an emission-line study of giant elliptical galaxies. In 2012, McDonald was named a Hubble postdoctoral fellow at the Kavli Institute for Astrophysics and Space Research at MIT.</p>
<p><strong>Andrei Neguţ</strong>, assistant professor in the Department of Mathematics, concentrates on problems in geometric representation theory, an area that overlaps studies in algebraic geometry and representation theory. His results connect to areas in mathematical physics, symplectic geometry, combinatorics and probability theory. His current research focuses on moduli of sheaves, quiver varieties, quantum algebras, and knot invariants. Neguţ received a PhD from Columbia University in 2015, studying under Andrei Okounkov. He completed a master’s in mathematics from Harvard University in 2012 and a BA from Princeton in 2009.</p>
<p><strong>Aaron Pixton</strong>, assistant professor in the Department of Mathematics, works on various topics in enumerative algebraic geometry, including the tautological ring of the moduli space of algebraic curves, moduli spaces of sheaves on 3-folds, and Gromov-Witten theory. Pixton was a three-time Putnam Fellow as an undergraduate at Princeton University, where he received his BA in mathematics in 2008. In 2009, Pixton completed Part III of the Mathematics Tripos at Cambridge University. He then returned to Princeton and completed his PhD in mathematics in 2013, studying under Rahul Pandharipande. That year, he received a five-year research fellowship from the Clay Mathematics Institute, and was appointed to a visiting postdoctoral fellowship at Harvard University.</p>
Kristen Bergmann, Davesh Maulik, Michael McDonald, Andrei Neguţ, and Aaron Pixton.Faculty, Mathematics, EAPS, Physics, School of Science, Kavli InstituteEthical trials, targeted ads
http://news.mit.edu/2015/optimize-outcomes-comparison-tests-0917
New method optimizes outcomes for subjects in comparison tests.Thu, 17 Sep 2015 09:30:00 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2015/optimize-outcomes-comparison-tests-0917<p>Clinical trials of new drugs or devices face a problem that most empirical inquiries don’t: They must not only provide clear data about toxicity and efficacy but also try to maximize the quality of treatment for all of the patients enrolled.</p>
<p>Online advertisers face a similar quandary. They want to test variants of ads to see which drive more traffic, but they also want the better-performing ads to reach more viewers.</p>
<p>In a forthcoming paper in the <em>Annals of Statistics</em>, Philippe Rigollet, an assistant professor of mathematics at MIT, and colleagues present a new way to organize such tests that’s mathematically guaranteed to yield the optimal result. Rigollet believes that the work could also have implications for the distribution of tasks in parallel computers.</p>
<p>“It’s called the ‘exploration-versus-exploitation dilemma,’” Rigollet says. “It was a bit of a dormant field in the ’80s and ’90s, and then in the early 2000s came Amazon and Google, and they had exactly this problem. In this paper, we looked at a variation of this thing that nobody, for some odd reason, had looked at.”</p>
<p>In principle, the best way to resolve the exploration-versus-exploitation dilemma for a given group of test subjects is to test one of them at a time. The first few subjects’ reactions to either of two drugs, for instance, could guide the treatment of the subsequent subjects. If, in the early going, one drug was clearly outperforming the other, it would be administered to the rest of the subjects, meeting the physician’s obligation to provide them with the best available treatment.</p>
<p>Of course, in a clinical trial, that approach would be woefully impractical, since it could take a year or more to determine each subject’s response to a new treatment. So clinical trials instead group subjects into batches. “People have started batching on the Internet as well, because it’s just too much to process,” Rigollet says. “There are so many people going on Google every second, they cannot wait to see what everybody’s doing.”</p>
<p><strong>Few regrets</strong></p>
<p>Rigollet and his collaborators — Vianney Perchet of the Université Paris Diderot, Sylvain Chassang of Princeton University, and Erik Snowberg of Caltech — show that with their technique, three or four batches of tests will generally yield results that are as good as those of testing subjects individually.</p>
<p>The measure of effectiveness they use is called “cumulative regret,” or the aggregate difference between the rewards that the subjects in the trial received — in the case of a drug trial, the mitigation of disease symptoms — and the rewards that they would have received had they all been administered what proved to be the best-performing option.</p>
<p>With a trial that tests subjects individually, the cumulative regret is proportional to the square root of the number of test subjects, or N<sup>0.5</sup>. With the researchers’ technique, four batches will at worst yield a cumulative regret proportional to N<sup>0.53</sup>, and three batches N<sup>0.57</sup>.</p>
<p>Those figures, however, assume that N can grow arbitrarily large. If it’s less than a million — which is almost always the case in clinical trials — then, in fact, just three batches will yield a cumulative regret proportional to N<sup>0.5</sup>. As the U.S. Food and Drug Administration currently requires four rounds of trials for new drugs, adopting the researchers’ scheme would not be a major disruption.</p>
<p><strong>Sizing up probabilities</strong></p>
<p>Moreover, Rigollet and his colleagues offer a principled way to determine the size of each batch. “The FDA requires four batches, but the number of people you have to take in each batch is not very well defined,” Rigollet says. “What our rule gives us is a way to say, ‘If you give me the number of patients you want to see, I can give you exactly the sizes of the batches you need to use.’”</p>
<p>The researchers’ approach is simple: After each batch, they calculate the uncertainty of its results. That uncertainty can be thought of as error bars around an average value. After the first phase of a clinical trial, for instance, 10 patients who took a new hepatitis drug for four weeks might have seen the virus count in their bloodstreams go down by an average of 50 percent. But statistically, because the sample size is so small, the true average for the population at large could be anywhere between 40 and 60 percent. Those values define the endpoints of the error bars.</p>
<p>In a trial comparing two drugs, if the error bars still overlap after any given round, both drugs continue into the next round; if they don’t, only the better-performing one continues. The same approach works for tests comparing more than two alternatives. Only those whose error bars overlap with the top-performing candidate continue from one round to the next.</p>
<p>For the researchers, the hard work wasn’t devising this protocol but proving its optimality — and determining how to size the batches. In ongoing work, they’re investigating trials that determine how different populations respond to different alternatives. It could be, for instance, that 20-year-old males and 50-year-old females would respond well to different ads for the same product.</p>
<p>The type of problem that Rigollet and his colleagues address is called a “bandit problem,” after “one-armed bandit,” a euphemism for slot machines. Someone trying to determine which of several slot machines offers the best rate of return without going broke in the process faces the exploration-versus-exploitation dilemma.</p>
<p>“This new result exhibits algorithms that adjust treatments only a very small number of times,” says Moritz Hardt, a research scientist at Google. “Surprisingly, as Rigollet and his co-authors elegantly prove, these algorithms still find a treatment that is nearly as good as the best single treatment in hindsight. This new development holds the promise of making bandit optimization a more robust choice across several application domains.”</p>
<p>Sébastien Bubeck, a researcher in the Theory Group at Microsoft Research, agrees. “There is little doubt that this new work will have an impact on how bandit algorithms are used in practice,” he says.</p>
<p>Rigollet’s work was funded by the National Science Foundation.</p>
Research, School of Science, Health sciences and technology, Mathematics, StatisticsA new molecular design approach
http://news.mit.edu/2015/new-molecular-design-approach-0911
New programming tool could help engineers build biologically inspired materials.Fri, 11 Sep 2015 11:15:01 -0400Kelsey Damrad | Department of Civil and Environmental Engineeringhttp://news.mit.edu/2015/new-molecular-design-approach-0911<p>For decades, materials scientists have worked to infuse the lessons learned from natural proteins into the design of new materials.</p>
<p>However, as the self-assembly process of many proteins remains unclear, our understanding of a material’s properties at a fundamental level and ways it can be translated into real-world use has provided a challenge.</p>
<p>Using a novel mathematical approach, a team of MIT researchers developed a domain-specific programming language for generating custom materials based on a set of design specifications. The software, dubbed Matriarch for “Materials Architecture”, allows users to combine and rearrange material building blocks in almost any conceivable shape.</p>
<p>The work suggests that engineers will be able to reach the next stage of materials design through fundamental control of a protein’s final assembled structure.</p>
<p>“Matriarch could very well be the core of a new molecular design process, where engineering decisions can be made at arbitrary scales,” says Department of Civil and Environmental Engineering (CEE) postdoc Tristan Giesa ’15, co-author of the study. “The idea is to start at ground level. If engineers require a polymer material to have specific properties — strength, resilience, size to name a few — then we need to question what must be done at a fundamental level to achieve these properties.”</p>
<p>With Matriarch engineers can explore what happens to a material’s properties when its architecture changes. Accessible as an open source Python library, the program will ultimately be used as a tool for engineers to quickly discover new materials and design them according to their needs.</p>
<p>“Our description of the material’s architecture is backed up by a rigorous mathematical framework, called category theory,” says David Spivak, co-author and research scientist in the Department of Mathematics. Category theory is a fairly new field of mathematics, focused on structural relationships and compositionality. The assembly process used by Matriarch was specified mathematically as a category-like structure, called an operad.</p>
<p>“We used the math as an inspiration to create a program that identifies the form of these hierarchical protein materials,” says Harvard University sophomore Ravi Jagadeesan, who collaborated as a high school student while enrolled in MIT's <a href="http://www.cee.org/research-science-institute" target="_blank">Research Science Institute</a> (RSI) program. Jagadeesan, writer of the majority of the software library, explained the code follows the mathematics very closely.</p>
<p>The MIT researchers — Giesa, Spivak, Jagadeesan, and CEE department head Professor Markus Buehler, the study’s senior author — published their findings In <a href="http://pubs.acs.org/doi/abs/10.1021/acsbiomaterials.5b00251" target="_blank"><em>ACS Biomaterials Science & Engineering</em></a>.</p>
<p><strong>A bottom-up design process</strong></p>
<p>Given a few basic building blocks and instructions, Matriarch builds hierarchical structures of proteins and generates atomic configurations. From these configurations, the program creates Protein Data Bank (PDB) files to be passed to molecular dynamics software.</p>
<p>The engineer can thus use Matriarch to perform building block substitutions, and structural changes, to study their effect on the functionality of a material.</p>
<p>“Our program is specialized on protein-based materials,” says Jagadeesan. “It allows us to replace the sequence of amino acids with anything we choose, and it also allows us to attach different sequences together or bend them in any conceivable shape. This decreases the computational time needed to determine the final structure of the material.”</p>
<p>The team tested their program on collagen protein — one of the most common building materials found in mammals, with a range of potential applications in synthetic design. With Matriarch, they developed a program to form natural triple-helical collagen molecules and alter the amino acid sequence. Mechanical tests on several mutations suggested that natural collagen could be optimized for stiffness and stability.</p>
<p>To perform this study with existing software would have been nearly impossible and time-intensive, says the team. Giesa says that synthesizing novel protein materials, such as collagen mutations, is currently quite challenging, especially in the chemistry lab.</p>
<p>Massively parallel simulation has opened new pathways for materials discovery, but it is still in its infancy. In the meantime, Matriarch will be a useful tool for the fast-growing materials engineering community.</p>
<p>The team is still expanding the functionality of the program, and they plan to systematically explore known proteins and how their subsequences organize themselves as building blocks on a variety of scales. Ultimately, they hope to create an extensible database of structures for engineers to estimate the final configuration that a new material or sequence will have.</p>
<p>“The more this program is used, the more it will gain in efficiency and accuracy,” Spivak says. The self-learning database, after running a stream of simulations, will record the protein’s preferred conformations and store the final structures.</p>
<p>“With this program, we are one step closer to defining the computational tools that form the basis for bottom-up materials engineering and providing the tools to quicken the process of discovering new materials,” Buehler says. “This type of program should be useful to many, will improve our ability to modify natural materials for other engineering applications, and enables engineers to apply category theory to solving real-world problems.”</p>
<p>Jagadeesan acknowledges support by the Research Science Institute program. Spivak acknowledges support by the Air Force Office of Scientific Research and the Office of Naval Research. Buehler and Giesa acknowledge support by the Office of Naval Research, the Army Research Office, and the National Institute of Health (NIH U01), as well as BASF North American Center for Research on Advanced Materials.</p>
Amyloidal structure created with the Matriarch software.Research, Civil and environmental engineering, School of Engineering, Mathematics, School of Science, Sustainability, National Institutes of Health (NIH)Untangling the mechanics of knots
http://news.mit.edu/2015/untangling-mechanics-knots-0908
New model predicts the force required to tie simple knots.Tue, 08 Sep 2015 00:00:01 -0400Jennifer Chu | MIT News Officehttp://news.mit.edu/2015/untangling-mechanics-knots-0908<p>Got rope? Then try this experiment: Cross both ends, left over right, then bring the left end under and out, as if tying a pair of shoelaces. If you repeat this sequence, you get what’s called a “granny” knot. If, instead, you cross both ends again, this time right over left, you’ve created a sturdier “reef” knot.</p>
<p>The configuration, or “topology,” of a knot determines its stiffness. For example, a granny knot is much easier to undo, as its configuration of twists creates weaker forces within the knot, compared with a reef knot. For centuries, sailors have observed such distinctions, choosing certain knots over others to secure vessels — largely by intuition and tradition.</p>
<p>Now researchers at MIT and Pierre et Marie Curie University in Paris have analyzed the mechanical forces underpinning simple knots, and come up with a theory that describes how a knot’s topology determines its mechanical forces.</p>
<p>The researchers carried out experiments to test how much force is required to tighten knots with an increasing number of twists. They then compared their observations with their theoretical predictions, and found that the theory accurately predicted the force needed to close a knot, given its topology and the diameter and stiffness of the underlying strand.</p>
<p>“This is the first time, to the best of our knowledge, that precision model experiments and theory have been tied together to untangle the influence of topology on the mechanics of knots,” the researchers write in a paper appearing in the journal <em>Physical Review Letters</em>.</p>
<p>Pedro Reis, the Gilbert W. Winslow Career Development Associate Professor in Civil Engineering and Mechanical Engineering, says the new knot theory may provide guidelines for choosing certain knot configurations for a given load-bearing application, such as braided steel cables, or surgical stitching patterns.</p>
<p>“Surgeons, of course, have a great deal of experience, and they know this knot is better for this stitching procedure than this knot,” Reis says. “But can we further inform the process? While maybe these knots are used, we might show that some other knots, done in a certain way, may be preferable.”</p>
<div class="cms-placeholder-content-video"></div>
<p><strong>A twisted theory</strong></p>
<p>Reis’ colleague, French theoretician Basile Audoly, originally took on the problem of relating a knot’s topology and mechanical forces. In previous work, Audoly, with his own colleague Sébastien Neukirch, had developed a theory based on observations of tightening a very simple, overhand knot, comprising only one twist. They then verified the theory with a slightly more complex knot with two twists. The theory, they concluded, should predict the forces required to tighten even more complex knots.</p>
<p>However, when Reis, together with his students Khalid Jawed and Peter Dieleman, performed similar experiments with knots of more than two twists, they found that the previous theory failed to predict the force needed to close the knots. Reis and Audoly teamed up to develop a more accurate theory for describing the topology and mechanics of a wider range of knots.</p>
<p>The researchers created knots from nitonol, a hyper-elastic wire that, even when bent at dramatic angles, will return to its original shape. Nitonol’s elasticity and stiffness are well known.</p>
<p>To generate various topologies, the researchers tied knots with multiple overhand twists, creating increasingly longer braids. They then clamped one end of each braid to a table, used a mechanical arm to simultaneously pull the knot tight, and measured the force applied. From these experiments, they observed that a knot with 10 twists requires about 1,000 times more force to close than a knot with just one.</p>
<p>“When Pedro Reis showed me his experiments on knots with as much as 10 twists, and told me that they could resist such a high force, this first appeared to me to be far beyond what simple equations can capture,” Audoly says. “Then, I thought it was a nice challenge.”</p>
<p><strong>From shoelaces to surgery</strong></p>
<p>To come up with a theory to predict the forces observed, Reis and Audoly went through multiple iterations between the experiments and theory to identify the ingredients that mattered the most and simplify the model. Eventually, they divided the problem in two parts, first characterizing the knot’s loop, then its braid. For the first part, the researchers quantified the aspect ratio, or shape of a loop, given the number of twists in a braid: The more twists in a braid, the more elliptical the loop.</p>
<p>The team then studied the forces within the braid. As a braid, or twist, is symmetric, the researchers simplified the problem by only considering one strand of the braid. </p>
<p>“Then we write an energy for the system that includes bending, tension, and friction for that one helical strand, and we are able to determine the shape,” Audoly says. “Once we have the shape, we can match it to this loop, and ultimately we get the overall force displacement response of the system.”</p>
<p>To test the theory, Reis plugged the experiments’ measurements into the theory to generate predictions of force.</p>
<p>“When we put the data through the machinery of the theory, the predictions and the dataset all collapse onto this master curve,” Reis says. “Once we have this master curve, you can give me a bending stiffness and diameter of a strand, and the number of turns in the knot, and I can tell you what force is required to close it. Also, we now understand how the knot locks itself up when more turns are added.”</p>
<p>Reis envisions multiple applications for the group’s theory, both significant and mundane.</p>
<p>“This theory helps us predict the mechanical response of knots of different topologies,” Reis says. “We’re describing the force it requires to close a loop, which is an indicator of the stiffness of the knot. This might help us to understand something as simple as how your headphones get tangled, and how to better tie your shoes, to how the configuration of knots can help in surgical procedures.”</p>
<p>This research was funded in part by the National Science Foundation.</p>
School of Engineering, Civil and environmental engineering, Mechanical engineering, Design, Materials science, Physics, Research, MathematicsSchool of Science announces 2015 Teaching Prizes for Graduate and Undergraduate Education
http://news.mit.edu/2015/school-science-teaching-prizes-0831
Mon, 31 Aug 2015 13:48:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2015/school-science-teaching-prizes-0831<p>The School of Science has announced the winners of its 2015 Teaching Prizes for Graduate and Undergraduate Education. The prizes are awarded annually to School of Science faculty members who demonstrate excellence in teaching in their courses for that year. Winners are chosen from nominations by their students or colleagues.</p>
<p>“MIT has the best students in the world and it is a privilege to teach them,” said Michael Sipser, dean of the School of Science. “I am delighted that we are celebrating these three outstanding educators in the School of Science.”</p>
<p><a href="http://math.mit.edu/directory/profile.php?pid=1461" target="_blank">Larry Guth</a>, professor of mathematics, was awarded a prize for graduate education for his subjects, 18.156 (Differential Analysis) and 18.S997 (The Polynomial Method). Guth’s nominators remarked on his infectious enthusiasm and his kindness and patience for his students, and were inspired by his dedication to the intellectual growth of his students. Several students said that Guth was among the best teachers they encountered in their undergraduate and graduate studies, citing in particular his teaching methods, which encouraged open-ended exploration of problems, curiosity and independent thought, and a solid understanding of the principles that underlie concepts and techniques.</p>
<p><a href="http://web.mit.edu/physics/people/faculty/ketterle_wolfgang.html" target="_blank">Wolfgang Ketterle</a>, the John D. MacArthur Professor of Physics, was awarded a prize for graduate education for his courses 8.421 (Atomic and Optical Physics) and 8.422 (Atomic and Optical Physics II). Ketterle’s nominators cited his ability to incorporate “a deep treatment of essential, subtle concepts” into a broad overview of atomic physics, to communicate concepts clearly through pictures, diagrams, and physical arguments rather than mathematical derivations alone, and to encourage students’ deep, independent exploration of the subject matter. The nominators further cited Ketterle for his evolving course design; Ketterle has continually modernized course material and experimented with new topics and teaching methods, while soliciting and responding to student feedback on changes. His nominators note they continue to use the MIT OpenCourseWare versions of both <a href="http://ocw.mit.edu/courses/physics/8-421-atomic-and-optical-physics-i-spring-2014/" target="_blank">8.421</a> and <a href="http://ocw.mit.edu/courses/physics/8-422-atomic-and-optical-physics-ii-spring-2013/" target="_blank">8.422</a> as resources, and “are sure that his courses will continue to benefit students both at MIT and elsewhere for many years to come.”</p>
<p><a href="https://www.broadinstitute.org/about/bios/bio-lander.html" target="_blank">Eric Lander</a>, the founding director of the Broad Institute and a professor of biology, was awarded the prize in undergraduate education for his course 7.00x (<a href="https://www.edx.org/course/introduction-biology-secret-life-mitx-7-00x-2#!" target="_blank">Introduction to Biology — The Secret of Life</a>), offered online through edX. Lander first hosted the course in 2013, after having taught it to MIT students in the classroom for 20 years. The online course has proven very popular, and required significant efforts to adapt it to online learning, including reworking the curriculum for students with limited backgrounds in biology, making supplemental videos for laboratory work, and incorporating computer-based protein and gene viewers so online students could see genes and proteins usually presented as models and illustrations in physical classrooms.</p>
<p>The School of Science welcomes Teaching Prize nominations for its faculty during the spring semester each academic year. For more information, please visit the school’s <a href="http://science.mit.edu/policies/teaching-prizes-graduate-and-undergraduate-education" target="_blank">website</a>.</p>
Larry Guth, Wolfgang Ketterle, and Eric LanderSchool of Science, Awards, honors and fellowships, Education, teaching, academics, Mathematics, Physics, Biology, Faculty, online learning, Massive open online courses (MOOCs), EdX, MITxSearching big data faster
http://news.mit.edu/2015/searching-big-data-faster-0826
Theoretical analysis could expand applications of accelerated searching in biology, other fields.Wed, 26 Aug 2015 12:00:00 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2015/searching-big-data-faster-0826<p>For more than a decade, gene sequencers have been improving more rapidly than the computers required to make sense of their outputs. Searching for DNA sequences in existing genomic databases can already take hours, and the problem is likely to get worse.</p>
<p>Recently, Bonnie Berger’s group at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) has been investigating <a href="http://newsoffice.mit.edu/2012/genetic-searching-algorithm-0710">techniques</a> to make biological and chemical data easier to analyze by, in some sense, <a href="http://www.nature.com/nbt/journal/v33/n3/full/nbt.3170.html">compressing</a> it.</p>
<p>In the latest issue of the journal <em>Cell Systems</em>, Berger and colleagues present a theoretical analysis that demonstrates why their previous compression schemes have been so successful. They identify properties of data sets that make them amenable to compression and present an algorithm for determining whether a given data set has those properties. They also show that several existing databases of chemical compounds and biological molecules do indeed exhibit them.</p>
<p>Given measurements for those properties, the researchers can also calculate the improvements in search efficiency that their compression techniques afford. For the data sets they analyze, those efficiencies scale sublinearly, meaning that the larger the data set, the more efficient the search should be.</p>
<p>“This paper provides a framework for how we can apply compressive algorithms to large-scale biological data,” says Berger, a professor of applied mathematics at MIT. “We also have proofs for how much efficiency we can get.”</p>
<p>The key to the researchers’ compression scheme is that evolution is stingy with good designs. There tends to be a lot of redundancy in the genomes of closely related — or even distantly related — organisms.</p>
<p>That means that of all the possible sequences of the four DNA letters — A, T, C, and G — only a very small subset is represented by the genomes of real organisms. Moreover, within the space of possible genomes, those of real organisms are not distributed randomly. Instead, they trace out continuous patterns, which represent the relatively slow rate at which species diverge.</p>
<p><strong>Birds of a feather</strong></p>
<p>To make searching more efficient, the Berger group’s compression algorithms cluster together similar genomic sequences — those that diverge by only a few DNA letters —then choose one sequence as representative of the cluster. A search can concentrate only on the likeliest clusters; most of the data never has to be examined.</p>
<p>If genomic data is envisioned as tracing a continuous path through a much larger space of possibilities, then the clusters can be envisioned as spheres superimposed on the data. Data points that fall within a single sphere are closely related.</p>
<p>Berger and her colleagues — first authors Noah Daniels, a postdoc in her group, and William Yu, a graduate student in applied mathematics, and David Danko, an undergraduate major in computational biology — show that data sets are amenable to their compressive search techniques if they meet two criteria. The first they refer to as metric entropy. This means that the data inhabits only a small part of the larger space of possibilities.</p>
<p>The second is low fractal dimension. That means that the density of the data points doesn’t vary greatly as you move through the data. If your search requires you to explore three spheres rather than one, it takes only three times as long — not 10 times, or 100 times.</p>
<p>In their paper, the MIT researchers analyze three data sets. Two describe proteins — one according to their sequences of amino acids, the other according to their shape — and the third describes organic molecules. In a separate paper, now under submission, the researchers apply the same types of analysis to DNA segments between 32 and 63 letters in length.</p>
<p><strong>Time’s arrow</strong></p>
<p>The efficiency of their search algorithm scales sublinearly, not with the number of data points, but with the metric entropy of the data set, which is a formal measure of the continuity of the data and their sparseness, relative to the space of possibilities. Because evolution is conservative, the metric entropy of genomic data should increase as new genomes are sequenced. That is, the addition of new genomes will not, in all likelihood, add new branches to the pattern traced out in the space of possibilities; rather, it will fill in gaps in the existing pattern, increasing the metric entropy.</p>
<p>Many other large data sets, however, could prove to be conservative in the same way. The range of behaviors exhibited by Web users, for instance, may, relative to the entire space of possibilities, be constrained by biology, by cultural history, or both. The MIT researchers’ compression techniques could thus be applicable to a wide range of data outside biology.</p>
<p>“The authors show that the local structure of genomics data can be exploited to speed up matching, by adopting a conceptually simple strategy,” says Lior Pachter, a professor at the University of California at Berkeley, whose appointments span the departments of mathematics, molecular and cell biology, and electrical engineering and computer science. “In empirical studies, they show via a number of examples that their strategy works. Moreover, they show that even a naive and simple approach to the hardest problem in the approach — finding the clusters — works well.”</p>
<p>“In my view, one interesting implication of the work that could be explored in future papers is the use of the coverings they produce to study the inherent structure of ‘omics’ data more carefully,” Pachter adds. “This may have applications not only to search but also to exploratory data analysis and statistical inference.”</p>
Illustration of points in an arbitrary high-dimensional space that live close to a one-dimensional, tree-like structure, as might arise from genomes generated by mutation and selection in evolution. Although high-dimensional at a fine scale, at the coarser scale of covering spheres, the data cloud looks nearly one-dimensional, which enables entropy scaling of similarity search.Research, School of Science, Algorithms, Biology, Computer science and technology, Data, Genetics, Mathematics, Computer Science and Artificial Intelligence Laboratory (CSAIL)Timing devices
http://news.mit.edu/2015/timing-devices-anna-mikusheva-0813
Anna Mikusheva refines the tools of time-series econometrics to develop better forecasting.Wed, 12 Aug 2015 23:59:59 -0400Peter Dizikes | MIT News Officehttp://news.mit.edu/2015/timing-devices-anna-mikusheva-0813<p>Ask enough scholars to explain their work, and sometimes surprising descriptions will emerge.</p>
<p>“My thesis was on the estimation of persistence, how much you remember from the past,” MIT Associate Professor Anna Mikusheva says of her PhD dissertation.</p>
<p>It may sound like Mikusheva is a psychologist or a Proust scholar. But she’s an econometrician: a scholar who studies the techniques of estimation used in economic models. More precisely, Mikusheva specializes in time-series econometrics, the subdiscipline that examines sequences of observations pertaining to a particular statistical output over time: inflation, gross domestic product, stock prices, and so on.</p>
<p>So when Mikusheva talks about “how much you remember,” she is being metaphorical about the key issue in time-series econometrics: To what extent are these discrete data points, like the history of a stock price, connected across time?</p>
<p>“Time series is exactly about time dependence, how different observations depend on each other,” Mikusheva explains.</p>
<p>Her work both analyzes existing economics tools in the domain, and helps to develop new techniques that can be applied to time-series problems. To fully account for the trajectory of something like inflation, of course, you need a thorough explanation of the various factors involved. But econometrics can help us see how solid such models are statistically — and how likely there is to be persistence and continuity in the processes that churn out economic data. For her innovative work and her teaching, Mikusheva was granted tenure at MIT earlier this year. </p>
<p><strong>Passing the test</strong></p>
<p>As it happens, Mikusheva’s personal journey, from a childhood in the Soviet Union to her position at MIT, is a time series with plenty of discontinuities in it. Among other things, she didn’t study economics as a student growing up in Orenburg, a Russian city in the Ural Mountains, near the border of Kazakhstan. </p>
<p>“It just happened that I liked math, from the beginning, from childhood,” Mikusheva says. “My teachers pushed me.” As she recalls it, her family provided additional moral support, though not necessarily academic direction.</p>
<p>“My parents were very supportive people who believed in education, but they didn’t know much about how education works, so they didn’t have much experience to know what to do,” Mikusheva says. “I had a very good teacher in math who thought that I had talent, so she pushed me to the Math Olympics, and so I competed a little bit on the regional level.”</p>
<p>Participating in the Math Olympics at age 15, Mikusheva didn’t get any farther than the regional level, but she caught a break while competing: Scouts from a boarding school in Moscow noticed her and offered her a spot at their academy, if she could pass the entrance exam.</p>
<p>Mikusheva passed the test, left home, and attended the school. “It was a rare opportunity,” she says.</p>
<p>Mikusheva then continued to Moscow State University, where she received her undergraduate degree in mathematics in 1998. Mikusheva began focusing formally on economics while receiving an MA at Moscow’s New Economic School and simultaneously finishing a PhD in math at Moscow State.</p>
<p>As it turned out, her graduate education was only about half-finished: She did well enough as a graduate student to enter Harvard University’s PhD program in economics. She entered intending to study game theory, but moved over to time-series econometrics, partly because her advisor, James Stock, had identified some problems Mikusheva thought she could address.</p>
<p>“It felt more natural to do econometrics,” Mikusheva reflects. “It’s mathematical statistics. I said, ‘That’s probably where my strength is.’”</p>
<p><strong>When “the data does not speak as loudly”</strong></p>
<p>Mikusheva was right: She finished her PhD in 2007, and her thesis, on a concept she developed known as “uniform asymptotic approximation,” was quickly published in a top journal. Many statistical techniques used for the evaluation of economic models are based on justifications assuming that the amount of data involved can grow infinitely. But economic data are not infinite, so how accurately do classical statistical methods perform when applied to real-world data? Mikusheva’s method shows where specific parts of models’ estimations might be less reliable than others — and indicates that a couple of common statistical methods in economics run into this reliability problem.</p>
<p>“As econometricians we are not developing models per se, but we are trying to develop methods that could be used by applied researchers, and I think as econometricians we do care about the quality of the methods we provide,” she says.</p>
<p>Since her initial success, Mikusheva has pursued multiple lines of research, with some converging around the notion of “weak identification” — the problem of having on a scarcity of information relating to part of an economic model. This is a particular problem for some macroeconomic (or large-scale) models, including those known as dynamic stochastic general equilibrium (DSGE) models.</p>
<p>“I have high opinions about my colleagues in other fields [of economics],” Mikusheva says. “Solving big macro models is quite a challenge, and do they do this quite successfully.” That said, she adds, “The difficulty with DSGE models is that data do not speak as loudly as we would wish.”</p>
<p>Now several years into her career, Mikusheva emphasizes how pleased she is to have landed at MIT.</p>
<p>“The department has been a very supportive environment,” Mikusheva observes. “It’s known to be one of the most cooperative departments. People like talking with each other.”</p>
<p>For Mikusheva, productive conversations also occur in the classroom: “I love teaching,” she says. “Sometimes [the students] teach me more than I teach them. I love discussion in class, and they often ask very interesting questions.”</p>
<p>For her efforts, Mikusheva was granted the MIT Economics Graduate Teacher of the Year award, in 2008. For her research, Mikusheva received the Elaine Bennett Research Prize from the American Economics Association in 2012, given biannually to a woman in economics who is within seven years of receiving her PhD.</p>
<p>In the immediate future, Mikusheva has more papers on weak identification in the publication pipeline, and she is continually looking at new areas of econometrics to explore. But whether there will be strong continuities between her past and future research — well, time will tell.</p>
Anna MikushevaFaculty, Profile, Economics, SHASS, Statistics, MathematicsHartley Rogers, Jr., professor emeritus of mathematics, dies at 89
http://news.mit.edu/2015/hartley-rogers-professor-emeritus-mathematics-dies-0722
Mathematician’s 53-year career at MIT included service as associate provost from 1974 to 1980.Wed, 22 Jul 2015 10:08:23 -0400Department of Mathematicshttp://news.mit.edu/2015/hartley-rogers-professor-emeritus-mathematics-dies-0722<p>Hartley Rogers, Jr., professor emeritus of mathematics at MIT, died at the Meadow Green Rehabilitation and Nursing Center in Waltham, Massachusetts, on Friday, July 17. He was 89.</p>
<p>Rogers joined the MIT mathematics faculty in 1956 as an assistant professor, following a year’s visit at MIT. He was promoted to full professor in 1964, and retired from MIT in 2009.</p>
<p>Rogers’ research interests were in mathematical logic, and he is credited as one of the main developers of recursion theory, and of the usefulness and validity of informal methods in this area. His 1959 paper “Computing Degrees of Unsolvability” obtained semantical completeness results for higher levels of arithmetical complexity, and underlies current methodology in studies of computable structures. Rogers authored the 1967 book “Theory of Recursive Functions and Effective Computability,” which has become a central and standard reference in the field, and remains in print.</p>
<p>Rogers served as vice president of the Association for Symbolic Logic, senior editor of the <em>Journal of Symbolic Logic,</em> senior editor of <em>Annals of Mathematical Logic,</em> and associate editor of the <em>Journal of Computer and Systems Sciences.</em> Among his distinctions, Rogers received the Lewis R. Ford Award of the Mathematical Association of America for his expository papers in 1965.</p>
<p>Rogers’ career at MIT included significant administrative service during the 1960s and 1970s. From 1962 to 1964, he was a member of the Committee on Curriculum Content Planning, whose report radically modified the General Institute requirements for undergraduate education. In 1968, he chaired the Panel on November Events and the MIT Community, whose findings further developed the judicial processes of the Institute. Rogers served as chair of the MIT faculty from 1971 to 1973, and as associate provost from 1974 to 1980. He chaired the editorial board of the MIT Press from 1974 to 1981, as the press became an arm of the Institute’s educational mission.</p>
<p>At Rogers’ suggestion in 1996, the Department of Mathematics initiated its Summer Program in Undergraduate Research (SPUR). Teams pair a graduate student mentor with an MIT undergraduate; each team then works intensively on a research problem over a six-week summer period, culminating with the undergraduate giving a presentation and submitting written materials to a group of math faculty. Under Rogers’ direction through 2006, SPUR became popular with students who saw its educational benefits.</p>
<p>In 2001, the Rogers family established the Hartley Rogers, Jr. Prize for the top SPUR teams selected by the faculty. The prize has not only boosted the competitive spirit of its participants, but has attracted participation by graduate students from Harvard University and exchange students from Cambridge University.</p>
<p>From 1993 to 2006, Rogers supervised the MIT mathematics section of the Research Summer Institute program for advanced high school students. From 1995 to 2008, he also helped develop the MIT problem-solving seminar into an important resource for students, especially freshmen, interested in participating in the William Lowell Putnam Mathematics Competition. (Each year, he invited all attendees to his home in Winchester, Massachusetts, for dinner prior to the competition.) During this period, MIT’s Putnam team placed among the top three teams 10 times, twice in first place.</p>
<p>Rogers was a popular and respected teacher, particularly with his development of course 18.022 (Multivariable Calculus with Theory). In 1993, he received the Teaching Prize for Undergraduate Education from the School of Science. Rogers’ graduate lectures in mathematical logic were known for their beauty and clarity, and he was known for assigning challenging problem sets. He produced 19 doctoral students at MIT, with 557 mathematical “descendants” in total.</p>
<p>“[Rogers] presented an innovative, intuitive approach to recursion theory (computability) in his lectures and classic text,” says Richard Shore, a professor of mathematics at Cornell University and former president of the Association for Symbolic Logic, who studied with Rogers as a PhD student under Gerald Sacks from 1968 to 1972. “His approach was a major influence on my development and on all other students of the subject for the past 50 years. He was both a gentleman and a scholar who was devoted to his students, university, and academic community. For me, personally, he was a model and mentor for professional conduct and service to the community for many years.”</p>
<p>Along with mathematics, Rogers maintained a love for English literature, the field of his undergraduate degree. In the 1960s, he took up rowing with a passion. He was a founding member of the Charles River All Star Has-Beens (CRASH-B) sprints, and served as its unofficial guru for three decades. He won numerous medals at the CRASH-B sprints as well as at World Rowing Masters competitions, and in the Head of the Charles Regatta. He was the president of Boston Rowing Center, which prepared many top athletes for the U.S. national team, in the 1980s and early 1990s.</p>
<p>Hartley Rogers, Jr., was born in Buffalo, New York, on July 6, 1926. He received his BA in English from Yale University in 1946. Following a year at Cambridge University as a Henry Fellow, he returned to Yale to complete his MS in physics in 1950. He continued his studies at Princeton University in mathematics, receiving his MA in 1951 and his PhD in 1952, with Alonzo Church was his thesis advisor. Rogers’ first academic appointment was as Benjamin Peirce Lecturer at Harvard from 1952 to 1955.</p>
<p>Rogers was a devoted father, fiercely proud of his children and their accomplishments. He is survived by his wife, Dr. Adrianne E. Rogers; by his three children, Hartley R. Rogers, Campbell D.K. Rogers, and Caroline R. Broderick; and by 10 grandchildren.</p>
<p>Gifts in Rogers’ memory may be made to the <a href="https://giving.mit.edu/givenow/ConfirmGift.dyn?desig=3633010" target="_blank">Hartley Rogers Jr. Fund</a> in the Department of Mathematics.</p>
Hartley Rogers, Jr. Mathematics, School of Science, Faculty, ObituariesLouis Howard, professor emeritus of mathematics, dies at 86
http://news.mit.edu/2015/louis-howard-professor-emeritus-mathematics-dies-0713
Influential mathematician and professor made fundamental contributions to subjects including hydrodynamic stability and geophysical flows.Mon, 13 Jul 2015 16:27:01 -0400Department of Mathematicshttp://news.mit.edu/2015/louis-howard-professor-emeritus-mathematics-dies-0713<p>Louis Norberg Howard, emeritus professor of mathematics at MIT, and McKenzie emeritus professor at Florida State University, died on Sunday, June 28, at the age of 86.</p>
<p>Howard joined the MIT mathematics faculty in 1955 as an assistant professor, and was promoted to full professor in 1964. He retired from MIT in 1984.</p>
<p>Howard was an applied mathematician who worked primarily in the field of fluid dynamics. He made fundamental contributions to a broad range of subjects, including hydrodynamic stability and geophysical flows. He made a number of key advances in our understanding of turbulent convection, flows in Hele-Shaw cells, salt-finger zones, rotating flows, and reaction-diffusion equations. The power of his mathematical modeling was evident when he transformed qualitative ideas about the bounds on turbulent transport into rigorous mathematical arguments that initiated the field of upper-bound theory.</p>
<p>While his background was in physics and applied mathematics, he had an exceptional command of pure mathematics, as evidenced by his existence proofs concerning the hydrodynamic equations, and his elegant Semicircle Theorem. His mathematical powers were highlighted when he generalized and simplified extensive previous work on the Richardson number criterion for shear flows. He also had a practical side, and was no stranger to either the laboratory or oceanographic field work. His rare combination of physical intuition and analytic power gave his work its characteristic physical relevance, breadth, and depth. </p>
<p>Howard was a scholar and a gentleman, beloved, admired and respected by all who knew him. He was a generous collaborator and mentor who shared his deep knowledge of fluid dynamics and applied mathematics with modesty and grace. He published widely with colleagues, postdocs, and students. He supervised nine PhDs at MIT, one at Princeton University, two at Florida State University, and he co-mentored several graduate students from other institutions. He continued his research long after retirement; his final paper is soon to appear in the <em>Journal of Fluid Mechanics</em>. </p>
<p>Howard was an inspiring teacher who taught a wide range of undergraduate and graduate subjects at MIT. He was fundamental to the successful expansion of MIT’s graduate program in applied mathematics. His time at MIT coincided with the expansion of the physical applied math group, of which he was a central figure. After MIT, Howard joined the faculty at Florida State University (FSU) in 1981 as professor of mathematics and affiliate professor of mechanical engineering. His departure for FSU was a great loss to the MIT scientific community. In 1986, he was appointed to the FSU Foundation Professorship, and he retired from FSU in 1996. His recent passing has been a blow to the international fluid mechanics community, which recognized him as one of its leading lights.</p>
<p>Howard had developed a long-term association with the Woods Hole Oceanographic Institution and was one of the original members of the Geophysical Fluid Dynamics (GFD) Summer Program in 1959, on whose steering committee he served from the early 1960s until 1984. Howard was the principal lecturer at GFD on several occasions, giving a series of advanced courses that helped establish the foundations of geophysical fluid dynamics. He supervised many GFD Fellows, and remained an active member of the WHOI GFD Summer School long after his retirement. Howard also built and maintained a cottage on Crooked Pond in Falmouth, Massachusetts, where he was a generous host to many.</p>
<p>Howard served as the representative of the American Mathematical Society on the U.S. National Committee on Theoretical and Applied Mechanics from 1979 to 1982, and on its Science Policy Committee from 1983 to 1987. In 1983 he was a member of the Council of the Fluid Dynamics Division of the American Physical Society. He served on the advisory board of Dynamical Systems Group of the Society of Industrial and Applied Mathematics from 1989 to 1991.</p>
<p>Howard was born in Chicago, Illinois, on March 12, 1929. He received his BA in physics from Swarthmore College in 1950, and his MA and PhD in mathematical physics from Princeton, in 1952 and 1953, respectively, under the supervision of Donald Spencer. He took an appointment as a Higgins lecturer in mathematics at Princeton in 1953, after which he became a research associate in mathematics and aeronautics at Caltech in 1955.</p>
<p>Howard was named a fellow of the American Academy of Arts and Sciences in 1965 and the American Physical Society in 1984, and was elected to the National Academy of Sciences in 1977. In 1997, he was honored with the prestigious Fluid Dynamics Prize of the American Physical Society.</p>
<p>Howard was married for almost 50 years to Alice G. S. Howard, with whom he had five children. They were divorced in 2000. Howard is survived by his ex-wife and four of his children, Astrid H. Howard, Emily A. Howard, Maxwell Carr-Howard and Holly H. Bjorklund.</p>
Louis HowardFaculty, Obituaries, Mathematics, School of ScienceHigh school students find their MathROOTS at MIT
http://news.mit.edu/2015/high-school-students-mathroots-0708
Program aims to inspire female and underrepresented minority students to pursue STEM fields.Wed, 08 Jul 2015 00:00:00 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2015/high-school-students-mathroots-0708<p>In a noisy MIT classroom last week, high school students eagerly speculated on the problems they might see in the team math competition they were about to begin. The MIT students serving as the competition’s judges passed out problem sets, shouting pleas for order above the din.</p>
<p>Out of the chaos, teams formed, and Tara Falt, a rising high school junior from Anaheim, California, was soon at the blackboard solving a problem.</p>
<p>Now the only sounds in the room were Falt’s voice, explaining every move in her solution, and the click of her chalk moving across the board. She had everyone’s rapt attention.</p>
<p>When she put the chalk down, both teams erupted into cheers. The judges awarded her full points.</p>
<p>The final session of the MIT MathROOTS program was off to a strong start.</p>
<p><strong>Encouragement in STEM</strong></p>
<p>Launched this year by MIT’s Program for Research in Mathematics, Engineering and Science (PRIMES) — an afterschool program for high school students — MathROOTS invited advanced high school students from underserved communities to develop their math skills at MIT. A total of 20 students spent 11 days — ending last Thursday — at the Institute, learning to solve Math Olympiad-style problems, as well as being introduced to special topics in mathematics.</p>
<p>MathROOTS was designed to encourage highly talented minority and female students to persist in their passion for science, technology, engineering, and mathematics (STEM) fields through college and beyond; to give them a sense of belonging; and to expose them to the kinds of advanced math that will keep them inspired.</p>
<p>“I’m proud that MIT has introduced this wonderful program,” says Michael Sipser, the Barton L. Weller Professor of Mathematics and dean of MIT’s School of Science, which provided funding for this summer’s program. “MathROOTS offers the real possibility of changing the lives of its participants, and through them, their communities. I hope that it will become a permanent offering for future extremely talented students, such as the ones we had the privilege of hosting this year.”</p>
<p><strong>“We’re all math geeks here” </strong></p>
<p>MathROOTS student Sofía Dudas had already attended one math enrichment program near her home in Seattle. Before that experience, Dudas was excited to spend six weeks on a university campus learning advanced math with 19 other students who were good at it — giving her a taste of college academics and social life.</p>
<p>But when she got there, Dudas was one of only three girls in the program, and the only Hispanic student. “I liked the math,” she says, but “I didn’t really connect with people. No one really talked to me for the first four weeks.”</p>
<p>But at MathROOTS, Dudas found a diverse group of students — and the deeper connection she had been missing previously. “We’re all math geeks here, and we all share the experience of being good at math, but also being the person who’s not supposed to be good at it,” she says. “Having this common tie has been really awesome.”</p>
<p>Before Dudas came to MathROOTS, she was hesitant about whether she should apply to MIT. She was worried that she wasn’t one of what she calls the “crazy geniuses” that she pictured attending MIT.</p>
<p>Dudas was also worried that going to MIT would repeat her lonely experience at the math camp in Washington: She didn’t want to be the only Latina in the room again.</p>
<p>Now that Dudas knows she’ll fit in at MIT, she says she will definitely apply for admission as an undergraduate. “This program opened some windows for me,” she says. “I realized if I work hard, I could be here.”</p>
<p><strong>Keeping top students engaged</strong></p>
<p>Quinton McArthur, the MathROOTS program director and associate director of admissions at MIT, says that it is essential to keep these students engaged, “and let them know that the community is welcoming, and that we’re invested in their excellence, just as we are in everyone else’s.”</p>
<p>Antonio Monreal, a MathROOTS participant from El Paso, Texas, relished the chance to deepen his knowledge of mathematics, and to approach it in more creative ways. Back home, his classes focus on learning math processes by rote, rather than learning why he should use those processes, or what the processes mean.</p>
<p>Monreal says that at MathROOTS, “They teach you an idea and you have to approach it in your own way. It’s more like an art, instead of a boring systematic thing. This way your only limit is your own imagination in making a beautiful proof.”</p>
<p>Students like Monreal — members of groups that are traditionally underrepresented on college campuses — often live in communities with limited access to courses in advanced math and science, as well as the kinds of enrichment programs that spark students’ interest in STEM fields and encourage them to pursue these fields after high school.</p>
<p><strong>“An eye-opener”</strong></p>
<p>Pavel Etingof, a professor of mathematics and faculty advisor to MathROOTS, believes that the program can help close the gap. MathROOTS focuses on Math Olympiad-style problems because they build on the kinds of mathematics that students have most likely encountered, but require a very different problem-solving approach. Not only are Math Olympiad problems much more fun, Etingof says, but they demand creativity and rigorous thinking, and encourage students to write proofs — challenges often missing from high school math.</p>
<p>“This is going to be an eye-opener for a lot of them,” Etingof says, “because they don’t have the opportunities back at home. If you want to build up representation in science and mathematics, we have to find these students and make sure that they get adequate exposure to math early in their life.”</p>
<p>When Monreal returns to high school this fall, there will be no more formal math instruction for him to take: He completed his high school’s most advanced math class this past spring, and doesn’t know of any enrichment programs available to him outside school.</p>
<p>“I know that I’m going to study a lot by myself, because I love math,” he said, “but there are no resources for me. I wish I knew about a program for people like me who don’t know what to do with talent or mathematical inclination.”</p>
<p>Etingof would like to see more programs like MathROOTS around the country. “MathROOTS cannot reach all of the talented minority and female high school students — like Antonio and Sofía — who need to be encouraged to stay in STEM fields, but who lack opportunities to build on their talents,” he says.</p>
<p>MathROOTS was modeled after a <a href="http://www.udc.edu/news/udc_hosting_training_for_pan_african_math_ibero_america_math_olympiads">training program</a> at the University of the District of Columbia for the Pan African and Ibero-America Math Olympiads. The program only lasted one year, but some of its participants later became students at MIT, inspiring McArthur — and his colleagues Matt McGann and Stu Schmill in MIT’s Office of Admissions — to revive the program at MIT. Working with Sipser, they found a home for the new program at MIT PRIMES.</p>
<p>MathROOTS students followed a curriculum designed and taught by head mentor Tanya Khovanova, an MIT lecturer in mathematics and the second woman to win the International Math Olympiad; and Yi Sun, a fourth-year mathematics graduate student and longtime competitor, and then tutor, in the Math Olympiad program. MIT PRIMES director Slava Gerovitch serves as MathROOTS’s academic director.</p>
School of Science, Mathematics, Contests and academic competitions, Diversity, Student life, Students, K-12 education, STEM education, education, Education, teaching, academics, Admissions, Women, Women in STEM, Program for Research in Mathematics, Engineering and Science (PRIMES)Modeling how thin films break up
http://news.mit.edu/2015/modeling-how-thin-films-break-up-rachel-zucker-0618
Recent PhD recipient Rachel Zucker models phenomena collectively known as "dewetting" in microscale to nanoscale thin films.
Thu, 18 Jun 2015 18:17:00 -0400Denis Paiste | Materials Processing Centerhttp://news.mit.edu/2015/modeling-how-thin-films-break-up-rachel-zucker-0618<p>Excess surface energy from unsatisfied bonds is a significant driver of dimensional changes in thin-film materials, whether formation of holes, contracting edges, or run-away corners. In general, this break-up of a material is known as dewetting. Recent MIT graduate Rachel V. Zucker, who received her PhD on June 5, has developed a range of mathematical solutions to explain various dewetting phenomena in solid films.</p>
<p>Working with collaborators at MIT as well as in Germany and Italy, Zucker, 28, developed a model for calculating fully-faceted edge retraction in two dimensions, but she says the crown jewel of her work is a phase field approach that provides a general method to simulate dewetting.</p>
<p>Thin-film materials range from about 1 micrometer (micron) down to just a few nanometers in thickness. Nanometer-scale films are the basic building blocks for circuit boards in electronic and electrochemical devices, and are patterned into wires, transistors, and other components. Zucker developed models for what happens to thin films over time. "They have a lot of surface area compared to their volume, just because they are so thin, especially in one dimension, and so that can actually amount to a huge driving force for the thin film to change its shape," she says.</p>
<p>At MIT, Zucker was co-advised by professors <a dir="ltr" href="http://dmse.mit.edu/faculty/profile/carter" target="_blank">W. Craig Carter</a> and <a dir="ltr" href="http://scripts.mit.edu/~cthomp/" target="_blank">Carl V. Thompson</a>. With dewetting, Zucker tackled one of the hard problems in materials science, Carter explains, especially with the addition of anistropic surface tension. "Equations start looking very complicated and the methods that you would you use to solve those equations start becoming more and more obscure. And so as you go down this path, you're going into terra incognita. How do you go about solving these problems?"</p>
<p>Dewetting of solid films looks like dewetting of a liquid — for example, water beading up on a windshield — but the material stays solid during this process. Solid-state dewetting can happen at temperatures well below the melting temperatures of the material when the film is very thin, and especially when it is patterned to make very small features like wires in integrated circuits. "Solid-state dewetting is getting to be more and more of a problem as we make things with smaller and smaller features," Thompson says.</p>
<p>Zucker studied both <a href="https://en.wikipedia.org/wiki/Isotropy" target="_blank">isotropic</a> materials, which exhibit the same properties in all directions, and <a href="http://en.wikipedia.org/wiki/Anisotropy" target="_blank">anisotropic</a> materials, which show different properties in different directions. Isotropic materials, which are usually glassy, are good materials to develop models, but are rarely used as engineering materials, she says. Common engineering materials such as metal, ceramic, or single-crystal thin films are usually anisotropic materials.</p>
<p>Zucker carried out stability analyses to understand the onset of the sometimes beautiful morphologies seen in experiments. "The big takeaway is: One, we can write down formulation of this problem; two, we can implement a numerical method to construct the solutions; three, we can make a direct comparison to experiments; and that strikes me as what a thesis should be — the complete thing — formulation, solution, comparison, conclusion," Carter says. Zucker defended her thesis, "Capillary-Driven Shape Evolution in Solid-State Micro- and Nano-Scale Systems," on April 13.</p>
<p>She says her breakthrough came in creating a geometric model of edge retraction. "I knew I wanted to do these stability analyses; I knew I wanted to understand the fingering instability and the corner instability, the Rayleigh instability, but I didn't know where to begin," Zucker says. When she recognized that she could generalize this geometry and use <a dir="ltr" href="http://www.wolfram.com/mathematica/" target="_blank">Wolfram Mathematica</a> to handle the algebra, she was able to apply it not only to edge retraction, but also to extend it to the fingering instability and corner instability. "I'd say that was a useful insight," she adds, but notes that it came not while working, but while running during a Christmas break. "Then all of sudden it hit me," she explains.</p>
<p><strong>Phase field approach</strong></p>
<p>For her doctoral research, Zucker examined film break-up during dewetting based on <a dir="ltr" href="https://en.wikipedia.org/wiki/Capillary_action" target="_blank">capillary action</a> for edge retraction and pinch-off, the fingering instability, the Rayleigh instability, and the corner instability. This capillary action occurs most dramatically at a region known as the triple line, where three phases meet, commonly the substrate, film being deposited, and atmosphere. The exception, which cannot be explained by capillary action alone, is hole formation, Zucker notes. With her phase field approach, Zucker says, "I don't have to make simplifying assumptions. I don't have to simplify the geometry, for example. It just treats the full problem. There have been I would say two previous simulation attempts, but ours is the first code that I would say is actually useful, because it's fast enough that it will run in a reasonable amount of time on a reasonable number of computer cores. So we can actually do science with it." Simulations that used to take a month on previous code can be reduced to about three days running her simulation, she explains.</p>
<p>"Rachel made very significant advances in our understanding of the fingering instability that develops along the edges of films as they undergo solid-state dewetting," Thompson says. "While people had speculated that the rims that form on these edges undergo a Rayleigh-like instability that leads to fingering, Rachel showed that a new instability she discovered, due to 'divergent retraction,' plays a dominant role. This allows better predictions of the length scales of structures that result from the dewetting process, and for how films might be modified to obtain structures with desired characteristics.</p>
<p>"Rachel also provided new and better explanations of the mechanisms that cause sharp corners in the edge of a retracting hole to run out ahead of other parts of the edge. Speculations in the literature focused on the role of long-range diffusion of material away from the corner, but Rachel showed that all the mass that is redistributed at the retracting tip of a corner is consumed locally in extending the length of the adjacent edges. This provided a fundamentally new way of thinking about evolution of the shapes of holes, and how that evolution might be controlled," Thompson explains.</p>
<p><strong>Modeling instabilities</strong></p>
<p>Zucker spent an extensive amount of time working on her doctorate in Germany, where she was hosted by Professor <a dir="ltr" href="http://www.mpie.de/3106007/group_leader1" target="_blank">Christina Scheu</a>, of the Max Planck Institute for Iron Research in Düsseldorf and the Ludwig-Maximilians University in Munich. Zucker spent about nine months in Munich followed by nine months in Düsseldorf. Zucker credits much of the code development work for phase field simulations of dewetting to Professor <a dir="ltr" href="http://tu-dresden.de/die_tu_dresden/fakultaeten/fakultaet_mathematik_und_naturwissenschaften/fachrichtung_mathematik/institute/wir/staff/Professoren/voigt_html" target="_blank">Axel Voigt</a> at the Technical University of Dresden in Germany, and postdoc Rainer Backofen. She also credits Professor Francesco Montalenti at the University of Milan-Bicocca in Italy, postdoc Roberto Bergamaschini, and PhD student Marco Salvalaglio with helping her learn how to use the code. While in Germany, she has also been working on microstructural optimization for energy materials.</p>
<p>"I wanted to work on these surface-energy-driven problems because they are so fundamental to materials science," Zucker explains. Carter connected Zucker with Thompson, whose group had been doing experiments focused on developing a better understanding of solid-state dewetting, both in order to prevent or suppress it in some cases, and also to develop new ways to control it to make specific patterns in other cases.</p>
<p>Zucker tackled various irregularities in thin-film formation, including Rayleigh instabilities, edge retraction, fingering, and corner instabilities. In the Rayleigh instability, for example, a cylinder of materials breaks up into isolated particles. The Rayleigh instability is a classical result that is now 137 years old. "Otherwise the other instabilities involved in dewetting of films haven't really been studied," Zucker says of her work. "I've done a lot of linear instability analyses to understand what wavelengths are going to be showing up in these instabilities, what length scales are we talking about and how that is connected to the film thickness."</p>
<p><strong>Solid-state dewetting</strong></p>
<p>The model Zucker developed for two-dimensional edge retraction for highly anisotropic, fully-faceted thin ﬁlms was published in 2013 in the journal <em>Comptes Rendus Physique</em> ("Proceedings of Physics"). Zucker's model was largely in accordance with experiments carried out by <a dir="ltr" href="http://scripts.mit.edu/~cthomp/index.php?option=com_content&view=article&id=96&Itemid=174" target="_blank">Alan Gye Hyun Kim</a> in Thompson's group on edge retraction of 130-nm-thick, single-crystal nickel ﬁlms on magnesium oxide (MgO). Zucker was also a co-author of Kim's 2013 experimental paper in the <em>Journal of Applied Physics.</em> Both experiments and model showed rims form as the edges retract.</p>
<p>In a fully-faceted film, the crystal material has facets similar to a jewel-cut diamond. Zucker, who studied four different orientations of the crystal structure, found that the diffusivity on the facet at the top of the rim has the largest inﬂuence on retraction, followed by influences from the other facets of the material. Both experiments and the model showed retraction distances varying by up to two times, depending on the edge orientation. The model was in closest agreement with experimental results for an (001) ﬁlm with an edge retracting in the (100) direction — varying by just 10 percent. However, Zucker's paper noted, the model over-estimated retraction distance for (001) ﬁlm retracting in the (110) direction and underestimated distance for an (011) ﬁlm retracting in the (110) direction. Zucker suggests the discrepancy between model and experiment could be accounted for by error in reported values of diffusivities for nickel facets and uncertainty about interfacial energy between the nickel film and magnesium oxide substrate. "The major factors which determine the retraction rate of a thin ﬁlm, according to this model, are: the ﬁlm thickness, the atomic diffusivity on the top facet and the angled facet, the equivalent contact angle of the ﬁlm on the substrate, and the absolute value of the surface energy. The edge retraction distance scales with the ﬁlm thickness h as h<sup>1/2</sup>," Zucker reported in "A model for solid-state dewetting of a fully-faceted thin film."</p>
<p><strong>WulffMaker software</strong></p>
<p>In a 2012 <a dir="ltr" href="http://dx.doi.org/10.1007/s10853-012-6739-x" target="_blank">paper</a>, Zucker presented a new method for finding the equilibrium shapes of faceted particles attached to a deformable surface. With Carter and three others, Zucker presented a suite of software tools to calculate these equilibrium shapes as well as for isolated particles and for particles attached to rigid interfaces. Their open-source code, <a dir="ltr" href="http://pruffle.mit.edu/wulffmaker/" target="_blank">WulffMaker</a>, is available as a Wolfram computable document format file or a Mathematica notebook. It is useful for modeling Wulff shapes for engineering materials such as alumina, as well as more complicated Winterbottom and double Winterbottom shapes. While the Wulff method models the simplest case of a uniform shape attaching to a level surface, the software also incorporates a new algorithm for calculating interfaces with more complicated angles of attachment and attachment to rigid substrates. The tool could be useful for analyzing electronic and optical devices produced from materials deposited on a substrate. The software combines interface energy data with geometric shape data and so can be used in reverse to calculate interface energy for abutting materials from experimentally obtained geometric data.</p>
<p>"This tool introduces a new computational method for finding shapes of minimal interface energy. It also helps to build intuition about the macroscopic properties of interfaces and their interactions, and aids in the quantitative measurement of interface energy densities, given a geometry. Properties such as the equivalent wetting angle, particle contact area, total energies, and distortions to the interface surrounding the particle are displayed by the software to enable further insight and analysis," Zucker wrote in her thesis.</p>
<p><strong>Teaching modules</strong></p>
<p>Besides her work in creating computerized models for thin film deformation, Zucker has been working with Carter on a new format to teach materials science that Carter calls proctored scaffolding. Unlike online instruction that allows students to passively consume information by watching videos or reading text, their approach is interactive and requires critical thinking. "The student can't just skate by without doing that critical thinking," Zucker explains.</p>
<p>Zucker used the method, which integrates the Wolfram Language, to teach 3.016 (Mathematics for Materials Science and Engineers) two years ago while Carter was on sabbatical. She has traveled internationally with Carter to demonstrate these <a dir="ltr" href="http://mpc-www.mit.edu/component/k2/item/537-materials-science-master-class" target="_blank">materials science master classes</a>. They also made a user interface tool for content developers, to make it easier for other instructors to create Mathematica notebooks.</p>
<p>A native of North Carolina, Zucker completed her bachelor's at MIT in 2009, receiving an outstanding senior award from the Department of Materials Science and Engineering. Zucker starts a three-year postdoctoral fellowship in July at the <a dir="ltr" href="http://millerinstitute.berkeley.edu" target="_blank">Miller Institute</a> at the University of California at Berkeley. She will be affiliated with both the mathematics and materials science departments. "I think ever since I was born I was going to be a professor," Zucker says.</p>
Rachel Zucker, Christina Scheu, Alexander MüllerResearch, Graduate, postdoctoral, Materials Science and Engineering, Materials science, Algorithms, Mathematics, Alumni/aeSchool of Engineering awards for 2015
http://news.mit.edu/2015/school-engineering-awards-2015
Awards were given to outstanding faculty, and graduate, and undergraduate students.Thu, 18 Jun 2015 00:00:00 -0400School of Engineeringhttp://news.mit.edu/2015/school-engineering-awards-2015<p>The MIT School of Engineering recently honored outstanding faculty, graduate, and undergraduate students, with the following awards:</p>
<p>Bose Award for Excellence in Teaching — given to a faculty member whose contributions have been characterized by dedication, care, and creativity:</p>
<ul>
<li><strong>Leslie Kaelbling</strong>, the Panasonic Professor of Computer Science and Engineering</li>
</ul>
<p>Junior Bose Award — for an outstanding contributor to education from among the junior faculty of the School of Engineering:</p>
<ul>
<li><strong>Katharina Ribbeck</strong>, the Eugene Bell Career Development Professor of Tissue Engineering in biological engineering</li>
</ul>
<p>Ruth and Joel Spira Awards for Excellence in Teaching — awarded to one faculty member each in three departments — electrical engineering and computer science, mechanical engineering, and nuclear science and engineering — to acknowledge “the tradition of high quality engineering education at MIT.” A fourth award rotates among the School of Engineering’s five other academic departments:</p>
<ul>
<li><strong>Jacopo Buongiorno</strong>, professor of nuclear science and engineering</li>
<li><strong>Tomás Palacios</strong>, associate professor of electrical engineering and computer science</li>
<li><strong>Srini Devadas</strong>, the Edwin Sibley Webster Professor in Electrical Engineering and Computer Science</li>
<li><strong>Sangbae Kim</strong>, assistant professor of mechanical engineering</li>
</ul>
<p>School of Engineering Graduate Student Award for Extraordinary Teaching and Mentoring — established in 2006 to recognize an engineering graduate student who has demonstrated extraordinary teaching and mentoring as a teaching or research assistant:</p>
<ul>
<li><strong>Joel Paulson</strong>, chemical engineering</li>
</ul>
<p>Capers and Marion McDonald Award for Excellence in Mentoring and Advising — to a faculty member who has demonstrated a lasting commitment to personal and professional development:</p>
<ul>
<li><strong>Daniel Blankschtein</strong>, the Herman P. Meissner (1929) Professor in Chemical Engineering</li>
</ul>
<p>The Barry M. Goldwater Scholarship — given to students who exhibit an outstanding potential and intend to pursue careers in mathematics, the natural sciences, or engineering disciplines that contribute significantly to technological advances in the United States:</p>
<ul>
<li><strong>Kaustav A. Gopinathan</strong>, electrical engineering and computer science </li>
<li><strong>Margaret G. Guo</strong>, electrical engineering and computer science and biological engineering</li>
<li><strong>Felipe Hernandez</strong>, mathematics</li>
<li><strong>Julia E. Page</strong>, chemistry</li>
</ul>
<p>The Henry Ford II Award — presented to a senior engineering student who has maintained a cumulative average of 5.0 at the end of their seventh term and who has exceptional potential for leadership in the profession of engineering and in society:</p>
<ul>
<li><strong>Taibo Li</strong>, electrical engineering and computer science</li>
</ul>
<p>Samuel M. Seegal Prize — awarded for excellence in teaching to a faculty member (or members) in the Department of Civil and Environmental Engineering, and/or the MIT Sloan School of Management, who inspires students in pursuing and achieving excellence:</p>
<ul>
<li><strong>Jerome Connor</strong>, a professor of civil and environmental engineering</li>
</ul>
Dean Ian A. Waitz and graduate student Joel PaulsonAwards, honors and fellowships, Students, Graduate, postdoctoral, Undergraduate, Faculty, Electrical Engineering & Computer Science (eecs), Mechanical engineering, Civil and environmental engineering, Chemical engineering, Biological engineering, Chemistry, Mathematics, School of Engineering, School of ScienceFour professors granted tenure in the School of Science
http://news.mit.edu/2015/four-professors-granted-tenure-school-science-0601
Mon, 01 Jun 2015 10:48:00 -0400School of Sciencehttp://news.mit.edu/2015/four-professors-granted-tenure-school-science-0601<p>The School of Science recently announced that four of its faculty members have been granted tenure by MIT.</p>
<p>This year’s newly tenured professors are:</p>
<p><a href="http://math.mit.edu/directory/profile.php?pid=1143">Laurent Demanet</a>, in the Department of Mathematics. Demanet studies inverse problems related to wave scattering and high-frequency data, which are often motivated by real-life challenges in seismic and radar imaging. Research directions include computational wave propagation, fast numerical algorithms, applied harmonic analysis, nonlinear signal processing, convex optimization, and the mathematics of sparse and separated expansions.</p>
<p>Demanet completed his undergraduate studies in mathematical engineering and theoretical physics at the University of Louvain in Belgium. After he completed his PhD in 2006 at Caltech under the direction of Emmanuel Candes, he was appointed the Szegö Assistant Professor at Stanford University. He joined the MIT faculty in the Department of Mathematics in 2009. In 2011, he received an Alred P. Sloan Research Fellowship and the Air Force Young Investigator Award. In 2012, he received a 2012 NSF CAREER Award.</p>
<p><a href="http://web.mit.edu/physics/people/faculty/gedik_nuh.html">Nuh Gedik</a>, the Lawrence C. (1944) and Sarah W. Biedenharn Career Development Associate Professor of Physics. Gedik uses advanced optical techniques for investigating and manipulating the properties of quantum materials, such as topological insulators and high-temperature superconductors. Using ultrafast laser pulses, he studies processes in solids that take place within femtoseconds (billionth of a millionth of a second) and at lengths of angstroms (tenth of a billionth of a meter). Gedik employs these techniques to search for answers to important problems in condensed matter physics, with a primary focus on understanding the mechanisms behind the unique properties of strongly correlated electron systems.</p>
<p>Gedik received his BS in physics in 1998 from Bogazici University in Istanbul, Turkey, and his PhD in physics in 2004 from the University of California at Berkeley. Following a postdoc appointment at Caltech, he joined the joined the faculty of MIT's Department of Physics in 2008. Gedik has received several awards and honors, including the Moore Experimental Investigator Award in Quantum Materials (2014), an Alfred P. Sloan Fellowship (2012), and an NSF CAREER Award (2009).</p>
<p><a href="http://web.mit.edu/physics/people/faculty/jarillo-herrero_pablo.html">Pablo Jarillo-Herrero</a>, the Mitsui Career Development Associate Professor of Physics. Jarillo-Herrero explores quantum transport in novel condensed-matter systems such as graphene, transition metal dichalcogenides, and topological insulators. In recent work, he has demonstrated the presence of a bandgap in graphene-based van der Waals heterostructures, novel quantum spin Hall and photothermoelectric effects in graphene, as well as light-emitting diodes, photodetectors, and solar cells in the atomically thin tungsten diselenide system. He has also made advances in characterizing and manipulating the properties of other ultrathin materials, such as ultra-thin graphite and molybdenum disulphide, which lack graphene’s ultrarelativistic properties, but possess other unusual electronic properties.</p>
<p>After earning an MS at the University of Valencia, Spain, in 1999 and another at the University of California at San Diego in 2001, Jarillo-Herrero earned his PhD at the Delft University of Technology in 2005. He remained at Delft for a year as a postdoc and then worked as a NanoResearch Initiative Fellow at Columbia University until he joined the MIT faculty in 2008. Jarillo-Hererro’s awards include an NSF Career Award (2008), an Alfred P. Sloan Fellowship (2009), the IUPAP Young Scientist Prize in Semiconductor Physics (2010), a DOE Early Career Award (2011), a Presidential Early Career Award for Scientists and Engineers (PECASE, 2012), an ONR Young Investigator Award (2013), and a Moore Foundation Investigator Award (2014).</p>
<p><a href="https://ono.mit.edu/">Shuhei Ono</a>, in the Department of Earth, Atmospheric and Planetary Sciences (EAPS). Ono is a geochemist who uses precise measurements of stable isotopes to address questions related to Earth’s early history, such as when oxygen first appeared in Earth’s atmosphere, the temperature of Earth’s early climate, and how far the biosphere extends into the Earth’s crust. Using state-of-the-art technology to unlock the isotopic signals for microbial, hydrothermal, and photochemical processes, his research group studies minerals formed billions of years ago or deep in the oceanic crust, as well as trace gasses from the atmosphere, cow rumens, and from the deep subsurface. </p>
<p>Ono earned his BS (1994) and ME (1996) at Waseda University in Tokyo, Japan, and PhD from Pennsylvania State University in 2001. He was a postdoctoral fellow at the Carnegie Institution of Washington. Ono joined EAPS as a faculty member in 2007. He was awarded the Jubilee Medal by the Geological Society of South Africa in 2006.</p>
Laurent Demanet, Nuh Gedik, Shuhei Ono, Pablo Jarillo-HerreroSchool of Science, Faculty, Awards, honors and fellowships, Physics, EAPS, MathematicsMeet the 2015 Goldwater Scholars
http://news.mit.edu/2015/meet-2015-goldwater-scholars-0526
Four MIT students honored for their academic achievements. Tue, 26 May 2015 10:48:01 -0400Leda Zimmerman | School of Engineeringhttp://news.mit.edu/2015/meet-2015-goldwater-scholars-0526<p>Four MIT juniors have been named recipients of Barry Goldwater Scholarship Awards for 2015-16. They were selected on the basis of academic merit from a field of 1,206 candidates nominated by university faculty nationwide. This year’s Goldwater Scholarship recipients are Kaustav A. Gopinathan, Margaret G. Guo, Felipe Hernandez, and Julia E. Page.</p>
<p>Gopinathan, majoring in electrical engineering and computer science (EECS), “is the most talented undergraduate student I have ever encountered … destined to be a scholar of the highest quality and I look forward to seeing his name in lights,” wrote one faculty member in his recommendation, adding “I typically do not write words of praise liberally.” Gopinathan, who has conducted research to develop a low-cost medical device for diagnosing anemia, and a signal processing technique for identifying apnea in newborns, intends to acquire both an MD and PhD. </p>
<p>Guo, a double major in EECS and biological engineering, hopes to perform research to increase understanding of biological systems, focusing “on engineering tractable models … for the purposes of supporting clinical decision making or improving biomedical systems and devices.” She got an early start on such research. In an internship with Medtronics, Guo helped to develop a new generation pacemaker, and in the lab of Linda Griffith, the School of Engineering Professor of Teaching Innovation and a professor of biological and mechanical engineering, Guo worked on image and statistical analysis tools used in an organ model for endometriosis.</p>
<p>Hernandez, majoring in mathematics, intends to pursue a PhD in this field and advance understanding between analysis, combinatorics, geometric measure theory, and materials science. One faculty advisor wrote that “what is really amazing is his ability to learn independently, and I believe that he is on track to become a first-rate research mathematician and scientist.”</p>
<p>Page, majoring in chemistry, plans to conduct research at the intersection of chemistry and medicine, focusing on diseases and the drugs used to treat them at the molecular level. One of Page’s recommendations concluded: “She is one of the most talented students I have met in more than two decades on the faculty at MIT. Julia has outstanding potential for leadership in a research career.” Page’s interest in biomedical research is motivated in part by her experience shadowing a radiation oncologist and engaging with cancer patients. Says Page, “I would like to have a career that combines research with some patient care.”</p>
<p>The Barry Goldwater Scholarship and Excellence in Education Program was established by Congress in 1986 to honor Senator Barry Goldwater, who served for 30 years in the U.S. Senate. The program is designed to encourage outstanding students to pursue careers in math, the natural sciences, and engineering. Recipients will receive stipends covering the cost of tuition, fees, books, and room and board up to a maximum of $7,500 per year.</p>
Julia Page, Felipe Hernandez, Kaustav Gopinathan, Margaret GuoAwards, honors and fellowships, Students, Undergraduate, Electrical Engineering & Computer Science (eecs), Biological engineering, Chemistry, Mathematics, School of Engineering, School of ScienceTo handle big data, shrink it
http://news.mit.edu/2015/algorithm-shrinks-big-data-0520
Algorithm reduces size of data sets while preserving their mathematical properties.Wed, 20 May 2015 00:00:01 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2015/algorithm-shrinks-big-data-0520<p>As anyone who’s ever used a spreadsheet can attest, it’s often convenient to organize data into tables. But in the age of big data, those tables can be enormous, with millions or even hundreds of millions of rows.</p>
<p>One way to make big-data analysis computationally practical is to reduce the size of data tables — or matrices, to use the mathematical term — by leaving out a bunch of rows. The trick is that the remaining rows have to be in some sense representative of the ones that were omitted, in order for computations performed on them to yield approximately the right results.</p>
<p>At the ACM Symposium on Theory of Computing in June, MIT researchers will present a new algorithm that finds the smallest possible approximation of the original matrix that guarantees reliable computations. For a class of problems important in engineering and machine learning, this is a significant improvement over previous techniques. And for all classes of problems, the algorithm finds the approximation as quickly as possible.</p>
<p>In order to determine how well a given row of the condensed matrix represents a row of the original matrix, the algorithm needs to measure the “distance” between them. But there are different ways to define “distance.”</p>
<p>One common way is so-called “Euclidean distance.” In Euclidean distance, the differences between the entries at corresponding positions in the two rows are squared and added together, and the distance between rows is the square root of the resulting sum. The intuition is that of the Pythagorean theorem: The square root of the sum of the squares of the lengths of a right triangle’s legs gives the length of the hypotenuse.</p>
<p>Another measure of distance is less common but particularly useful in solving machine-learning and other optimization problems. It’s called “Manhattan distance,” and it’s simply the sum of the absolute differences between the corresponding entries in the two rows.</p>
<p><strong>Inside the norm</strong></p>
<p>In fact, both Manhattan distance and Euclidean distance are instances of what statisticians call “norms.” The Manhattan distance, or 1-norm, is the first root of the sum of differences raised to the first power, and the Euclidean distance, or 2-norm, is the square root of the sum of differences raised to the second power. The 3-norm is the cube root of the sum of differences raised to the third power, and so on to infinity.</p>
<p>In their paper, the MIT researchers — Richard Peng, a postdoc in applied mathematics, and Michael Cohen, a graduate student in electrical engineering and computer science — demonstrate that their algorithm is optimal for condensing matrices under any norm. But according to Peng, “The one we really cared about was the 1-norm.”</p>
<p>In matrix condensation — under any norm — the first step is to assign each row of the original matrix a “weight.” A row’s weight represents the number of other rows that it’s similar to, and it determines the likelihood that the row will be included in the condensed matrix. If it is, its values will be multiplied according to its weight. So, for instance, if 10 rows are good stand-ins for each other, but not for any other rows of the matrix, each will have a 10 percent chance of getting into the condensed matrix. If one of them does, its entries will all be multiplied by 10, so that it will reflect the contribution of the other nine rows it’s standing in for.</p>
<p>Although Manhattan distance is in some sense simpler than Euclidean distance, it makes calculating rows’ weights more difficult. Previously, the best algorithm for condensing matrices under the 1-norm would yield a matrix whose number of rows was proportional to the number of columns of the original matrix raised to the power of 2.5. The best algorithm for condensing matrices under the 2-norm, however, would yield a matrix whose number of rows was proportional to the number of columns of the original matrix times its own logarithm.</p>
<p>That means that if the matrix had 100 columns, under the 1-norm, the best possible condensation, before Peng and Cohen’s work, was a matrix with hundreds of thousands of rows. Under the 2-norm, it was a matrix with a couple of hundred rows. That discrepancy grows as the number of columns increases.</p>
<p><strong>Taming recursion</strong></p>
<p>Peng and Cohen’s algorithm condenses matrices under the 1-norm as well as it does under the 2-norm; under the 2-norm, it condenses matrices as well as its predecessors do. That’s because, for the 2-norm, it simply uses the best existing algorithm. For the 1-norm, it uses the same algorithm, but it uses it five or six times.</p>
<p>The paper’s real contribution is to mathematically prove that the 2-norm algorithm will yield reliable results under the 1-norm. As Peng explains, an equation for calculating 1-norm weights has been known for some time. But “the funny thing with that definition is that it’s recursive,” he says. “So the correct set of weights appears on both the left-hand side and the right-hand side.” That is, the weight for a given matrix row — call it <em>w</em> — is set equal to a mathematical expression that itself includes <em>w</em>.</p>
<p>“This definition was known to exist, but people in stats didn’t know what to do with it,” Peng says. “They look at it and think, ‘How do I ever compute anything with this?’”</p>
<p>What Peng and Cohen prove is that if you start by setting the <em>w</em> on the right side of the equation equal to 1, then evaluate the expression and plug the answer back into the right-hand <em>w</em>, then do the same thing again, and again, you’ll quickly converge on a good approximation of the correct value of <em>w</em>.</p>
<p>“It’s highly elegant mathematics, and it gives a significant advance over previous results,” says Richard Karp, a professor of computer science at the University of California at Berkeley and a winner of the National Medal of Science and of the Turing Award, the highest honor in computer science. “It boils the original problem down to a very simple-to-understand one. I admire the mathematical development that went into it.”</p>
Research, School of Science, School of Engineering, Algorithms, Computer science and technology, Data, Mathematics, Computer Science and Artificial Intelligence Laboratory (CSAIL), Electrical Engineering & Computer Science (eecs)Boiling down viscous flow
http://news.mit.edu/2015/predict-patterns-viscous-fluids-0423
A new simplified model predicts patterns that form from honey-like fluids.Wed, 22 Apr 2015 23:59:59 -0400Jennifer Chu | MIT News Officehttp://news.mit.edu/2015/predict-patterns-viscous-fluids-0423<p>Drizzling honey on toast can produce mesmerizing, meandering patterns, as the syrupy fluid ripples and coils in a sticky, golden thread. Dribbling paint on canvas can produce similarly serpentine loops and waves.</p>
<p>The patterns created by such viscous fluids can be reproduced experimentally in a setup known as a “fluid mechanical sewing machine,” in which an overhead nozzle deposits a thick fluid onto a moving conveyor belt. Researchers have carried out such experiments in an effort to identify the physical factors that influence the patterns that form.</p>
<p>Now a group of mathematicians at MIT, Cambridge University, and elsewhere have developed a simple model to predict patterns formed by viscous fluids as they fall onto a moving surface.</p>
<p>The researchers looked at four patterns — sinusoidal waves; repeating and alternating loops; and straight lines — and observed that the pattern formed depends on the ratio between the fluid’s speed on impact and the speed of the conveyor belt. The team found that this ratio influences a fluid’s shape, or curvature, just before hitting the surface, which in turn determines the pattern that forms.</p>
<p>The team used its model to create simulations of viscous flow; these simulations matched the patterns produced in previous experiments by others.</p>
<p>The simple geometrical model may be easily integrated into computer graphics simulations to create realistic videos of viscous liquids like honey and oil. The model may also be used to optimize manufacturing processes for products such as nonwoven materials — synthetic fabrics that are manufactured through an injection process that sprays polymers onto a conveyor belt, in patterns meant to resemble woven textiles.</p>
<p>Pierre-Thomas Brun, an instructor in MIT’s Department of Mathematics, says the geometrical model provides a simple method to both predict and create patterns from viscous fluids.</p>
<p>“We’re getting at the core of pattern formation, and explaining why transitions from pattern to pattern occur, with a very minimalistic model,” Brun says. “With this method, you can have a 3-D printer inject your polymer and just move the belt at the appropriate speed, and you can get the patterns you want.”</p>
<p>Brun and his colleagues have published their results this week in the journal <em>Physical Review Letters</em>.</p>
<p><strong>“Boiling down” viscous flow</strong></p>
<p>In 2012, researchers at the University of Toronto carried out a fluid mechanical sewing machine <a href="https://www.youtube.com/watch?v=CMYISqxS3K4">experiment</a>, drizzling a viscous fluid onto a progressively slowing conveyor belt. The experiment showed that as the belt starts, moving rapidly, the fluid forms a straight line as it hits the surface. As the belt slows, the fluid, flowing at the same rate, starts to meander in a wavelike pattern, then form alternating loops, and then finally, repeating loops, as the conveyor belt grinds almost to a halt.</p>
<p>Brun and others have studied these experimental results, and have since come up with a detailed numerical model, called “discrete viscous robes numerics,” to describe the resulting patterns, depending on factors such as fluid height, viscosity, and gravity. But Brun says this model, though precise in its predictions, contains many equations that are complex to solve.</p>
<p>Instead, he and his group sought to “boil down” the dynamics of viscous flow into a simpler, workable model, mainly by doing away with a complex variable: inertia, an object’s resistance to any change in motion. For instance, in the case of the fluid mechanical sewing machine, the rotation of the thread generates centrifugal forces in the coil that forms on the conveyor belt.</p>
<p>Brun chose to model the system without inertia, in a scenario in which fluid flows from a very small height — a scenario in which the fluid stretches under the force of gravity, but inertia does not play a role. Under these conditions, he observed that the patterns formed were the same as those created with the full, inertia-driven numerical model — a sign that something other than inertia was determining pattern formation.</p>
<p><strong>Digging into the “heel” of the problem</strong></p>
<p>Brun and his colleagues found that the crux of the issue came down to what they termed the “heel” of the flow — the point just before impact, when a fluid curves slightly, forming a heel-like shape. The researchers found that the patterns formed on the conveyor belt depend on the shape of the fluid heel. They noted the shape, or curvature, of the heel was determined by the distance and orientation between two points: the point at which the fluid first contacts the surface, and the point directly below the nozzle.</p>
<p>These two properties shape the curvature of the fluid as it hits the belt. The group also found that the resulting curvature determines the new angle and impact point of the fluid — a phenomenon that induces a “memory” effect in the fluid.</p>
<p>“Memory is usually induced by inertia, but despite the fact that here there is no inertia, we still maintain this idea of memory, which is essential for formation of patterns,” Brun says. “It’s really embedded in these geometry features. Otherwise, the patterns would just be random.”</p>
<p>Brun and his colleagues used their model to simulate the fluid mechanical sewing machine scenario, changing the shape of the heel in response to the speed of the conveyor belt. They produced four main patterns — waves, straight lines, and alternating and repeating loops — that matched the patterns generated by the more detailed numerical model.</p>
<p>The researchers say their simplified model may be geared toward optimizing a novel class of microfabrication techniques for manufacturing extremely small, tailorable textured fibers.</p>
<p>“We now have a very powerful tool we can use to get to the core of the experiment, to get deeper into the way these patterns are formed,” Brun says.</p>
<p>Dominic Vella, an associate professor of applied mathematics at Oxford University, says, “What is really important and elegant about this paper is that they have reduced the problem to a much simpler formulation. This means that they are able to gain new understanding of the process, especially the crucial role of geometry.”</p>
<p>Vella, who was not involved with the research, sees multiple applications for the model.</p>
<p>“It could be a useful practical tool for understanding how fast telecommunications cables can be laid down, and at the other end of the spectrum, what parameter regimes should be used to obtain a particular pattern in nonwoven textiles,” he says. “At the frivolous end, perhaps one could make an iPhone app that would tell you how fast to ice a cake to get a given pattern.”</p>
<p>This research was funded in part by the European Research Council.</p>
Researchers use numerical simulations to predict different patterns that may form as viscous threads fall onto a moving belt. Computer science and technology, Industry, Manufacturing, Materials science, Mathematics, Physics, Research, School of ScienceEight faculty members elected to the American Academy of Arts and Sciences
http://news.mit.edu/2015/eight-faculty-members-elected-american-academy-arts-and-sciences-0422
Among 197 elected this year to the prestigious honorary society.Wed, 22 Apr 2015 10:00:00 -0400News Officehttp://news.mit.edu/2015/eight-faculty-members-elected-american-academy-arts-and-sciences-0422<div class="field field-name-field-article-content field-type-text-long field-label-hidden">
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<p>Eight MIT faculty members are among 197 leaders from academia, business, public affairs, the humanities, and the arts elected to the American Academy of Arts and Sciences, the academy <a href="https://www.amacad.org/content/news/pressReleases.aspx?pr=10233">announced today</a>.</p>
<p>One of the nation’s most prestigious honorary societies, the <a href="https://www.amacad.org/default.aspx">academy</a> is also a leading center for independent policy research. Members contribute to academy publications, as well as studies of science and technology policy, energy and global security, social policy and American institutions, the humanities and culture, and education.</p>
<p>Those elected from MIT this year are:</p>
<ul>
<li>Sangeeta N. Bhatia, the John J. and Dorothy Wilson Professor of Health Sciences and Technology</li>
<li>Robert E. Cohen, the Raymond A. and Helen E. St. Laurent Professor of Chemical Engineering</li>
<li>Thomas J. Greytak, the Lester Wolfe Professor Emeritus of Physics</li>
<li>Sally Haslanger, the Ford Professor of Philosophy</li>
<li>John D. Joannopoulos, Francis Wright Davis Professor of Physics</li>
<li>William P. Minicozzi II, a professor of mathematics</li>
<li>Kathleen Thelen, the Ford Professor of political science</li>
<li>Iván Werning, the Robert M. Solow Professor of Economics</li>
</ul>
<p>“We are honored to elect a new class of extraordinary women and men to join our distinguished membership,” Don Randel, chair of the academy’s Board of Directors, said in a statement. “Each new member is a leader in his or her field and has made a distinct contribution to the nation and the world. We look forward to engaging them in the intellectual life of this vibrant institution.”</p>
<p>The new class will be inducted at a ceremony held on Oct. 10 at the academy’s headquarters in Cambridge.</p>
<p>Since its founding in 1780, the academy has elected leading “thinkers and doers” from each generation, including George Washington and Benjamin Franklin in the 18th century, Daniel Webster and Ralph Waldo Emerson in the 19th century, and Albert Einstein and Winston Churchill in the 20th century. The current membership includes more than 250 Nobel laureates and more than 60 Pulitzer Prize winners.</p>
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Faculty, Awards, honors and fellowships, AAAS, Electrical Engineering & Computer Science (eecs), Chemical engineering, Physics, Philosophy, Mathematics, Political science, EconomicsAdding up to a big win
http://news.mit.edu/2015/students-win-putnam-math-competition-0410
MIT dominates at annual Putnam Mathematical Competition, taking five of six top individual spots.Thu, 09 Apr 2015 23:59:59 -0400Helen Knight | MIT News correspondenthttp://news.mit.edu/2015/students-win-putnam-math-competition-0410<p>It’s official: MIT students “rock” at math.</p>
<p>MIT swept the board at this year’s prestigious William Lowell Putnam Mathematical Competition, winning the team award and placing five students among the top six individual spots, an achievement that earns each the title of “Putnam Fellow.”</p>
<p>The Putnam competition, the premier undergraduate mathematics contest in the U.S. and Canada, is notoriously tough: The median score for the latest exam, held last Dec. 6, was just three points out of a possible 120; more than half of the participants did not solve a single problem fully.</p>
<p>This makes the overall performance of MIT’s students all the more remarkable, according to Michael Sipser, the Barton L. Weller Professor of Mathematics and dean of the School of Science.</p>
<p>“This year’s fantastic and unprecedented performance by MIT’s undergraduate math stars continues our increasingly amazing results over the past decade on the William Lowell Putnam Mathematical Competition,” Sipser says. “Congratulations to the team and to our other high scorers and to all contestants. MIT math rocks!”</p>
<p>This year 4,320 students from 557 colleges and universities across the U.S. and Canada took part in the competition, including 431 teams. Of these, 32 out of the 89 top individual scorers were MIT students, including the five Putnam Fellows: senior Zipei Nie, freshman Mark Sellke, sophomore Bobby Shen, sophomore David H. Yang, and sophomore Lingfu Zhang.</p>
<p>Nie and Yang were also members of the winning MIT team, alongside junior Mitchell M. Lee. MIT will receive a $25,000 award, while each team member will receive $1,000. Teams from Harvard University and Rensselaer Polytechnic Institute followed MIT, finishing in second and third place, respectively.</p>
<p>The results of this year’s competition are a tangible sign of the exceptional ways in which students succeed in their endeavors, according to Tomasz Mrowka, the Singer Professor of Mathematics and head of the Department of Mathematics at MIT. “The heart of MIT is the exceptional people that go about their endeavors with passion and creativity mixed with a heavy dose of intelligence,” Mrowka says. “The mathematics department is very proud of our students.”</p>
<p>The Putnam competition, which was established in 1938 and is held every year on the first Saturday in December — with results announced approximately four months later — consists of 12 problems, each worth 10 points, and lasts for six hours over two equal sessions.</p>
<p>The competition is designed to reward quick thinkers, says Bjorn Poonen, the Claude E. Shannon Professor of Mathematics at MIT and one of just eight contestants ever to be a four-time Putnam Fellow — in Poonen’s case, as a Harvard undergraduate from 1985 to 1988.</p>
<p>This year, Poonen was MIT’s faculty coordinator for the competition, and also taught course 18.A34 (Problem Solving Seminar) to help freshmen prepare for the exam.</p>
<p>“The competition is more like the 400-meter dash than a marathon, since in mathematics research most discoveries are made only after a much longer effort,” Poonen says. “The hardest problem this year was solved by none of the 4,320 participants.”</p>
<p>Although not all mathematicians perform well in such timed competitions, many past winners have gone on to have distinguished careers in mathematics and other fields, with a few even winning a Fields Medal or Nobel Prize, Poonen says.</p>
<p>The competition is open to all undergraduates, whether or not they are math majors, he says. “But most of the top scorers are students who have had prior experience with math competitions in high school, or who have practiced by working through Putnam problems from previous years.”</p>
<p>Sellke, a math major at MIT and one of this year’s Putnam Fellows, scored 96 out of the possible 120 points in the exam. He says his experience in high-school math competitions undoubtedly helped him to do well in the exam. “In fact, all six of this year’s Fellows have previously earned gold medals at the International Mathematical Olympiad for high-school students,” he says.</p>
<p>Shen, another Putnam Fellow, attributes his success in the competition to writing clear solutions to the easiest eight of the 12 problems. “A common sentiment about the Putnam is that graders are pretty strict on the easy problems, and that losing points is as inevitable as snow in Boston in February,” Shen says. “So while others rush through the exam, I'll just keep defining my variables, lemmas, and edge cases as carefully as I can, and hopefully keep cashing in.”</p>
<p>Each of the six Putnam Fellows will receive an award of $2,500. The next 10 highest individual scorers in the competition, five of whom were MIT students, will receive a prize of $1,000.</p>
<p>“Our department classes focus teaching on the deeply rich subjects of mathematics, as well as methods for applying these ideas to solve mathematical, scientific, or engineering problems,” says Sipser, a former head of MIT’s Department of Mathematics.</p>
<p>“Our success at the Putnam competition is mostly due to the incredible students that choose to come to MIT,” he adds. “We do train them for the competition, and I am sure that helps, but more important is the talent and drive of the students.” </p>
(Left to right) junior Mitchell Lee, sophomore Bobby Shen, mathematics professor Bjorn Poonen, freshman Mark Sellke, and sophomore Lingfu ZhangMathematics, School of Science, Awards, honors and fellowships, Contests and academic competitions, Students, UndergraduateFalling in love with numbers at MIT
http://news.mit.edu/2015/awm-winner-sheela-devadas-number-lover-0403
Sheela Devadas '15, winner of the 2015 Alice T. Schafer Prize for Excellence in Mathematics, fell in love with the subject at MIT — while still in high school.Fri, 03 Apr 2015 13:13:01 -0400Elizabeth Thomson | MIT Spectrumhttp://news.mit.edu/2015/awm-winner-sheela-devadas-number-lover-0403<p>Sheela Devadas was 15 when she was first exposed to representation theory and other subfields of mathematics as a participant in <a href="http://math.mit.edu/research/highschool/primes/index.php" target="_blank">PRIMES</a>, MIT’s Program for Research in Mathematics, Engineering and Science for high-school students. Later that fall she was a finalist in the <a href="http://mathprize.atfoundation.org/index" target="_blank">Advantage Testing Foundation</a>’s Math Prize for Girls, <a href="https://newsoffice.mit.edu/2011/math-prize-girls-0920" target="_self">hosted that year</a> by MIT. </p>
<p>Fast forward to Devadas’s final semester as an MIT senior. Just months away from graduating with a degree in math — and completing her undergraduate studies in only three years — Devadas traveled to San Antonio, Texas, to accept the 2015 Alice T. Schafer Prize for Excellence in Mathematics from the <a href="http://sites.google.com/site/awmmath/home" target="_blank">Association for Women in Mathematics</a>. She is also co-author of a <a href="http://projecteuclid.org/euclid.jca/1420466343" target="_blank">paper on representation theory</a> that appeared in the Winter 2014 issue of the <em>Journal of Commutative Algebra.</em> </p>
<p>PRIMES was formative in Devadas’ decision to pursue math as a career (she will be starting graduate school this fall, although she does not yet know where). “I already knew I was interested in math when I started PRIMES, but it was definitely what convinced me that academia was my goal. I got a sense of what math research was actually like.”</p>
<p>Her advice for incoming MIT students who like math but aren’t sure if they want to major in it? “I would definitely recommend taking math classes beyond General Institute Requirements. Some of them are a lot of fun and they give you a better sense of what math is like than the required calculus classes might.”</p>
<p>Devadas is the sixth person from MIT to win the Schafer prize in the 25 years it has been awarded. Past award recipients are Fan Wei ’12, who won the prize in 2012; Charmaine Sia ’10, co-winner in 2010; Maria Monks ’10, who won in 2009; Galyna Dobrovolska ’09, who won in 2008; and Ruth Britto-Pacumio ’96, who won in 1995.</p>
<p>Read about other students’ experiences with PRIMES, <a href="http://math.mit.edu/research/highschool/primes/testimonials/index.php" target="_blank">in their own words</a>.</p>
Sheela Devadas and Ruth CharneyMathematics, Awards, honors and fellowships, STEM, STEM education, Classes and programs, Women, K-12 education, Students, Undergraduate, School of ScienceFive MIT researchers win Sloan Research Fellowships
http://news.mit.edu/2015/sloan-research-fellowships-0302
Faculty specializing in mathematics, chemistry, mechanical engineering, and economics among 126 selected.Mon, 02 Mar 2015 17:15:00 -0500News Officehttp://news.mit.edu/2015/sloan-research-fellowships-0302<p>Two mathematicians, a chemist, a mechanical engineer, and an economist from MIT are among the 126 American and Canadian researchers awarded 2015 Sloan Research Fellowships, the Alfred P. Sloan Foundation recently announced.</p>
<p>New MIT-affiliated Sloan Research Fellows are: Jörn Dunkel, an assistant professor of mathematics; Emmy Murphy, an assistant professor of mathematics; Bradley Pentelute, the Pfizer-Laubauch Career Development Assistant Professor of Chemistry; Themistoklis Sapsis, an assistant professor of mechanical engineering; and Heidi Williams, the Class of 1957 Career Development Assistant Professor of Economics.</p>
<p>Awarded annually since 1955, the Sloan Research Fellowships are given to early-career scientists and scholars whose achievements and potential identify them as rising stars among the next generation of scientific leaders. This year’s recipients are drawn from 57 colleges and universities across the United States and Canada.</p>
<p>“The beginning of a one’s career is a crucial time in the life of a scientist. Building a lab, attracting funding in an increasingly competitive environment, and securing tenure all depend on doing innovative, original high-quality work and having that work recognized,” said Paul L. Joskow, president of the Alfred P. Sloan Foundation, in a press release. “For more than 50 years the Sloan Foundation has been proud to celebrate the achievements of extraordinary young scientists who are pushing the boundaries of scientific knowledge.”</p>
<p>Administered and funded by the foundation, the fellowships are awarded in eight scientific fields: chemistry, computer science, economics, mathematics, evolutionary and computational molecular biology, neuroscience, ocean sciences, and physics. To qualify, candidates must first be nominated by fellow scientists and subsequently selected by an independent panel of senior scholars. Fellows receive $50,000 to be used to further their research.</p>
<p>For a complete list of this year’s winners, visit: <a href="http://www.sloan.org/fellowships/2015-sloan-research-fellows/">http://www.sloan.org/fellowships/2015-sloan-research-fellows/</a></p>
<p>For more information on the Alfred P. Sloan Foundation, visit: <a href="http://www.sloan.org/">http://www.sloan.org/</a></p>
School of Science, School of Engineering, SHASS, Awards, honors and fellowships, Mathematics, Chemistry, Mechanical engineering, Economics, Sloan fellows, FacultyWrinkle predictions
http://news.mit.edu/2015/predicting-wrinkles-fingerprints-curved-surfaces-0202
New mathematical theory may explain patterns in fingerprints, raisins, and microlenses.Mon, 02 Feb 2015 11:00:00 -0500Jennifer Chu | MIT News Officehttp://news.mit.edu/2015/predicting-wrinkles-fingerprints-curved-surfaces-0202<p>As a grape slowly dries and shrivels, its surface creases, ultimately taking on the wrinkled form of a raisin. Similar patterns can be found on the surfaces of other dried materials, as well as in human fingerprints. While these patterns have long been observed in nature, and more recently in experiments, scientists have not been able to come up with a way to predict how such patterns arise in curved systems, such as microlenses.</p>
<p>Now a team of MIT mathematicians and engineers has developed a mathematical theory, confirmed through experiments, that predicts how wrinkles on curved surfaces take shape. From their calculations, they determined that one main parameter — curvature — rules the type of pattern that forms: The more curved a surface is, the more its surface patterns resemble a crystal-like lattice.</p>
<p>The researchers say the theory, reported this week in the journal <em>Nature Materials,</em> may help to generally explain how fingerprints and wrinkles form.</p>
<p>“If you look at skin, there’s a harder layer of tissue, and underneath is a softer layer, and you see these wrinkling patterns that make fingerprints,” says Jörn Dunkel, an assistant professor of mathematics at MIT. “Could you, in principle, predict these patterns? It’s a complicated system, but there seems to be something generic going on, because you see very similar patterns over a huge range of scales.”</p>
<p>The group sought to develop a general theory to describe how wrinkles on curved objects form — a goal that was initially inspired by observations made by Dunkel’s collaborator, Pedro Reis, the Gilbert W. Winslow Career Development Associate Professor in Civil Engineering.</p>
<p><a href="http://newsoffice.mit.edu/2014/morphable-surfaces-could-cut-air-resistance-0624">In past experiments</a>, Reis manufactured ping pong-sized balls of polymer in order to investigate how their surface patterns may affect a sphere’s drag, or resistance to air. Reis observed a characteristic transition of surface patterns as air was slowly sucked out: As the sphere’s surface became compressed, it began to dimple, forming a pattern of regular hexagons before giving way to a more convoluted, labyrinthine configuration, similar to fingerprints.</p>
<p>“Existing theories could not explain why we were seeing these completely different patterns,” Reis says.</p>
<p>Denis Terwagne, a former postdoc in Reis’ group, mentioned this conundrum in a Department of Mathematics seminar attended by Dunkel and postdoc Norbert Stoop. The mathematicians took up the challenge, and soon contacted Reis to collaborate.</p>
<p><strong>Ahead of the curve</strong></p>
<p>Reis shared data from his past experiments, which Dunkel and Stoop used to formulate a generalized mathematical theory. According to Dunkel, there exists a mathematical framework for describing wrinkling, in the form of elasticity theory — a complex set of equations one could apply to Reis’ experiments to predict the resulting shapes in computer simulations. However, these equations are far too complicated to pinpoint exactly when certain patterns start to morph, let alone what causes such morphing. </p>
<p>Combining ideas from fluid mechanics with elasticity theory, Dunkel and Stoop derived a simplified equation that accurately predicts the wrinkling patterns found by Reis and his group.</p>
<p>“What type of stretching and bending is going on, and how the substrate underneath influences the pattern — all these different effects are combined in coefficients so you now have an analytically tractable equation that predicts how the patterns evolve, depending on the forces that act on that surface,” Dunkel explains.</p>
<p>In computer simulations, the researchers confirmed that their equation was indeed able to reproduce correctly the surface patterns observed in experiments. They were therefore also able to identify the main parameters that govern surface patterning.</p>
<p>As it turns out, curvature is one major determinant of whether a wrinkling surface becomes covered in hexagons or a more labyrinthine pattern: The more curved an object, the more regular its wrinkled surface. The thickness of an object’s shell also plays a role: If the outer layer is very thin compared to its curvature, an object’s surface will likely be convoluted, similar to a fingerprint. If the shell is a bit thicker, the surface will form a more hexagonal pattern.</p>
<p>Dunkel says the group’s theory, although based primarily on Reis’ work with spheres, may also apply to more complex objects. He and Stoop, together with postdoc Romain Lagrange, have used their equation to predict the morphing patterns in a donut-shaped object, which they have now challenged Reis to reproduce experimentally. If these predictions can be confirmed in future experiments, Reis says the new theory will serve as a design tool for scientists to engineer complex objects with morphable surfaces.</p>
<p>“This theory allows us to go and look at shapes other than spheres,” Reis says.<br />
“If you want to make a more complicated object wrinkle — say, a Pringle-shaped area with multiple curvatures — would the same equation still apply? Now we’re developing experiments to check their theory.”</p>
<p>This research was funded in part by the National Science Foundation, the Swiss National Science Foundation, and the MIT Solomon Buchsbaum Fund.</p>
MIT researchers have developed a mathematical equation that predicts how surface patterns form on curved objects. Pictured is a sphere with a combination of hexagons and labyrinthine patterns, and a more complex, torus-shaped object with hexagonal dimples.Materials science, Mathematics, Mechanical engineering, Civil and environmental engineering, School of Science, School of Engineering, ResearchProfessor emeritus Richard Schafer, former deputy head of mathematics at MIT, dies at 96
http://news.mit.edu/2015/professor-emeritus-richard-schafer-former-deputy-head-mathematics-dies-0115
Thu, 15 Jan 2015 11:54:20 -0500Department of Mathematicshttp://news.mit.edu/2015/professor-emeritus-richard-schafer-former-deputy-head-mathematics-dies-0115<p>Richard D. Schafer, emeritus professor and former deputy head of the MIT Department of Mathematics, died on Dec. 28, 2014. He was 96.</p>
<p>Schafer joined the MIT mathematics faculty in 1959 as deputy head under department head William Ted Martin. The department had seen a period of rapid growth of faculty and postdoctoral programs in the ’50s, with expanding demands in teaching and graduate supervision. As deputy head, Schafer was instrumental in organizing the application and review processes of the relatively new CLE Moore Instructorship program, and in systemizing the assignment of teaching and the scheduling of classes with the Office of the Registrar. He stepped down as deputy head when Ted Martin ended his tenure as department head in 1968, but he stayed on at MIT until his retirement in 1988 as professor emeritus.</p>
<p>Schafer was an algebraist, an expert in non-associative algebras. He did collaborative work with fellow mathematician Claude Chevalley on Lie algebras and extensive work on Jordan algebras. In 1966, Schafer published “Introduction to Nonassociative Algebras” (Academic Press), a book that has served as a standard reference for many years.</p>
<p>Schafer was born in Buffalo, New York, in 1918. He received both a BA and an MA from the University of Buffalo, and a PhD in mathematics from the University of Chicago in 1942. Between 1942 and 1945 he served in the U.S. Naval Reserve.</p>
<p>Upon his return to academia in 1945, Schafer took a yearlong appointment as an instructor at the University of Michigan. He was a member of the Institute for Advanced Study from 1946-48 and later from 1958-59. He joined the faculty at the University of Pennsylvania in 1948, and moved to the University of Connecticut as a full professor in 1953, where he served as department head until joining MIT in 1959. From 1955-58, Schafer also served as associate secretary of the eastern region of the American Mathematical Society.</p>
<p>In 2013, Schafer was elected to join the inaugural class of fellows of the American Mathematical Society. He had been active for 50 years in the Mathematical Association of America and Phi Beta Kappa.</p>
<p>A lifelong opera fan, Schafer regularly traveled to the Metropolitan Opera in New York City and to the Salzburg Festival in Germany. For 67 years, he was married to the late Alice T. Schafer — a fellow mathematician and longtime professor at Wellesley College, and a co-founder of the Association for Women in Mathematics.</p>
<p>Schafer is survived by sons John D. Schafer of Turner, Maine, and Richard S. Schafer of Concord, Massachusetts; grandson Scott D. Schafer of Philadelphia, Pennsylvania; granddaughters Tania Murray of Frankfort, Illinois and Stephanie Altavilla of Chelsea, Massachusetts; and two great-grandchildren, Mikayla and Grant Murray.</p>
Richard SchaferObituaries, Faculty, Mathematics, School of ScienceSchool of Science welcomes seven new professors this spring
http://news.mit.edu/2015/school-science-welcome-seven-new-professors-spring-0114
Wed, 14 Jan 2015 18:15:01 -0500School of Sciencehttp://news.mit.edu/2015/school-science-welcome-seven-new-professors-spring-0114<p>The School of Science welcomes seven new assistant professors in the departments of Biology, Chemistry, Mathematics, and Physics. Their research spans topics from the mathematics of machine learning to the precision control of DNA transcription and translation to the search for exotic subatomic particles.</p>
<p>“I am delighted to welcome these young new mathematicians and scientists to our faculty at MIT,” said Michael Sipser, dean of the School of Science and the Barton L. Weller Professor of Mathematics. “They carry on the great tradition of extraordinary research in the School of Science.”</p>
<p><strong>Semyon Dyatlov, mathematics</strong><br />
Before joining the faculty, <a href="http://math.mit.edu/~dyatlov/" target="_blank">Semyon Dyatlov</a> came to the Department of Mathematics as a Clay Research Fellow in 2013. He received his PhD from the University of California at Berkeley in 2013, under the guidance of Maciej Zworski. Dyatlov uses the methods of microlocal analysis to study problems in scattering theory, in particular questions regarding scattering resonances. The two principal applications of his work concern decay of waves on black-hole spacetimes (where resonances are known as quasi-normal modes) and decay of correlations for Anosov and Axiom A flows (and the corresponding Pollicott-Ruelle resonances).</p>
<p><strong>Nikta Fakhri, physics</strong><br />
Combining approaches from physics, biology, and engineering, Nikta Fakhri seeks to understand the principles of active matter. Active matter is prominent in biology and is generally understood as a class of non-equilibrium systems in which microscopic components dissipate energy and thereby collectively organize to generate motions and forces on mesoscopic scales. As an important example of biological active matter, Fakhri will study the cell nucleus, in which the control and processing of genetic material is orchestrated by an intricate interplay of a large number of non-equilibrium processes. Fakhri will develop novel probes, such as single-walled carbon nanotubes, to map the organization and dynamics of non-equilibrium heterogeneous materials. In addition, she will use biology as inspiration for designing pluripotent materials that change their properties and functions in response to external stimuli. Fakhri joins the Department of Physics after a postdoctoral fellowship, supported by the Human Frontier Science Program, in the physics department at the University of Göttingen in Germany. In 2002, she received her BS in chemical and petroleum engineering from Sharif University of Technology in Tehran, Iran. She completed her PhD in chemical and biomolecular engineering at Rice University in 2011.</p>
<p><strong>Vadim Gorin, mathematics</strong><br />
<a href="http://math.mit.edu/directory/profile.php?pid=1415" target="_blank">Vadim Gorin</a> works on asymptotic representation theory, studying various properties of representations of groups linked into series — such as unitary groups, orthogonal groups, or symmetric groups — as the rank tends to infinity. In a related work on mathematical statistical mechanics and probability theory, Gorin focuses on 2-D lattice models, random matrices, and interacting particle systems. Before his appointment as assistant professor, Gorin came to MIT as a CLE Moore Instructor in 2012. In 2011, he earned his PhD in mathematics from Utrecht University, under the direction of Grigori Olshanski, Erik P. van den Ban, and Alexander Gnedin. He became a candidate of sciences in mathematics at Moscow State University, under the direction of Grigori Olshanksi and Boris Gurevich.</p>
<p><strong>Gene-Wei Li, biology</strong><br />
<a href="https://biology.mit.edu/people/gene_wei_li" target="_blank">Gene-Wei Li</a> aims to elucidate the physical and quantitative principles behind the precise control of transcription and translation of DNA. His central research questions include how cells fine-tune their RNA and protein production in the right amounts to form stoichiometric complexes; how the amount of protein production is connected with the physiology of the entire cell; and how misregulation can have detrimental effects. Li joins the Department of Biology following a postdoctoral fellowship at University of California at San Francisco. He received his PhD in physics from Harvard University in 2010 and his BS in physics from the National Tsinghua University in Taiwan in 2004.</p>
<p><strong>Phillipe Rigollet, mathematics</strong><br />
Phillipe Rigollet works at the intersection of statistics, machine learning, and optimization, focusing primarily on the design and analysis of statistical methods for high-dimensional problems. His recent research focuses on the statistical limitations of learning under computational restraints. At the University of Paris VI, Rigollet earned a BS in statistics in 2001, a BS in applied mathematics in 2002, and a PhD in mathematical statistics in 2006. He has held positions as a visiting assistant professor at the Georgia Institute of Technology and then as an assistant professor at Princeton University.</p>
<p><strong>Gabriela Schlau-Cohen, chemistry</strong><br />
<a href="http://www.schlaucohenlab.com/people/" target="_blank">Gabriela Schlau-Cohen</a>’s research employs single-molecule and ultrafast spectroscopies to explore the energetic and structural dynamics of biological systems. Schlau-Cohen works to develop new methodology to measure ultrafast dynamics on single proteins, which will be a means to study systems with both sub-nanosecond and second dynamics. In other research, she merges optical spectroscopy with model membrane systems to provide a novel probe of how biological processes extend beyond the nanometer scale of individual proteins. One application of these approaches will be exploring the underlying mechanisms of photosynthetic light harvesting. To understand these mechanisms, experiments will probe both the heterogeneity of the individual proteins and how they are wired together to produce efficient and adaptive systems. Schlau-Cohen joins the Department of Chemistry after a postdoctoral fellowship at Stanford University. She received her BS from Brown University in 2003 and her PhD in chemistry from the University of California at Berkeley in 2011.</p>
<p><strong>Lindley Winslow, physics</strong><br />
Lindley Winslow is an experimental nuclear physicist whose primary focus is on neutrinoless double-beta decay. Neutrinoless double-beta decay is an extremely rare nuclear process which, if it is ever observed, would show that the neutrino is its own antiparticle, a Majorana particle. A Majorana neutrino would have profound consequences to particle physics and cosmology, among them an explanation of the universe’s matter-antimatter symmetry. Winslow takes part in two projects that search for double-beta decay at CUORE (Cryogenic Underground Observatory for Rare Events) and KamLAND-Zen, and works to develop new, more sensitive double-beta decay detectors. Winslow received her BA in physics and astronomy in 2001 and her PhD in physics in 2008, both from the University of California at Berkeley. After a postdoctoral fellowship at MIT, she was appointed as an assistant professor at the University of California at Los Angeles. Winslow has also been awarded a 2010 L’Oréal for Women in Science Fellowship.</p>
MIT School of Science professorsFaculty, Biology, Chemistry, Mathematics, Physics, School of ScienceOf yeast, ecology, and cancer
http://news.mit.edu/2014/yeast-ecology-and-cancer-jeff-gore-1229
Jeff Gore’s work with baker’s yeast helps ecologists respond to trends, like vanishing fisheries and collapsing honeybee colonies.Mon, 29 Dec 2014 13:27:01 -0500http://news.mit.edu/2014/yeast-ecology-and-cancer-jeff-gore-1229<p>A physicist, a mathematician, and an economist walk into a bakery. It sounds like the opening of a witty one-liner, but for Jeff Gore, the Latham Family Career Development Assistant Professor of Physics at MIT, it marks the beginning of a career.</p>
<p>Gore — who actually is a physicist, mathematician, and economist (he also studied electrical engineering and computer science at MIT as an undergraduate and studied biophysics as a graduate student at the University of California at Berkeley) — now uses his observations of the behavior of baker’s yeast as a way to translate heady theories about evolution and ecology into practical indicators that an ecosystem is headed for a change. His work is already beginning to help field biologists and ecologists detect and respond to troubling environmental trends such as vanishing fisheries and collapsing honeybee colonies.</p>
<p>“There are a lot of really beautiful ideas in theoretical ecology but it’s difficult to test those ideas with any sort of experiment,” says Gore. “We see an exciting opportunity to take our experimentally tractable microbial communities and do theoretically motivated experiments.”</p>
<p>Gore’s approach to the study of ecology and evolution is guided by the idea that complex systems, such as populations of living organisms, follow universal patterns of behavior. Those patterns can be expressed mathematically with formulas that exhibit special features, such as stable states and tipping points. A tipping point, a phenomenon popularized by Malcolm Gladwell in his book, "The Tipping Point," is a critical moment of change, such as the moment when a pot of water accumulates enough heat to boil, or, more alarmingly, the moment the atmosphere accumulates enough heat that climate patterns shift irreversibly.</p>
<p>Tipping points occur in populations of organisms that cooperate to survive. For instance, baker’s yeast collectively breaks sucrose into smaller sugars that can be used as fuel. This team effort helps stabilize the population by ensuring there is enough fuel to go around. “But if the population gets too small, it can’t break down enough sugar to survive,” says Gore. “The population collapses.”</p>
<p>Gore’s studies of thriving yeast colonies and colonies under duress have uncovered telling signs that a colony is on the verge of tipping into oblivion. In one study, Gore and colleagues found that colonies nearing a tipping point take longer to recover from challenges, such as an influx of salt that substantially slows the growth of the yeast population. “The recovery time grows as you get closer to the tipping point,” says Gore. “We can measure this in the lab with yeast.”</p>
<p>This recovery slowdown isn’t just a phenomenon seen in baker’s yeast. Rather, it will occur in other populations with similar cooperative foundations, such as packs of wolves that hunt collectively, schools of fish that travel together, or colonies of bees that work together. Because of this universality, a slowdown in recovery could become an early warning that a population is on the verge of collapse. “It may be possible to anticipate that a tipping point is approaching before we cross that threshold, which is important because once a threshold is crossed, it can be very difficult to reverse,” says Gore.</p>
<p>Recently, Gore and graduate student Lei Dai have begun applying these findings in collaboration with Christina Grozinger, a honeybee biologist at Pennsylvania State University. Honeybee colonies are collapsing at an alarming rate worldwide and researchers have been looking for new ways to approach understanding and preventing colony collapse disorder. In unpublished work, the researchers found that honeybee colonies need a critical mass of bees to survive. “Smaller colonies all collapse,” says Gore.</p>
<p>The work is a first step towards applying the warning signs Gore sees in yeast to natural ecosystems and even complex biological systems, such as cancer. “Depending on the population you’re talking about, you either want it to collapse or not,” he says. “In the case of a tumor, we do.”</p>
<p>In an effort to create laboratory experiments that more closely resemble natural ecosystems, Gore is beginning to work with microbial colonies that involve more than one species. “We want to understand how the dynamics play out when we have more complex communities,” he says.</p>
Jeff GorePhysics, Mathematics, Ecology, Economics, Biology, School of Science, Faculty, Profile, CancerTomasz Mrowka named head of the Department of Mathematics
http://news.mit.edu/2014/tomasz-mrowka-named-head-department-mathematics-1210
Wed, 10 Dec 2014 13:01:01 -0500Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/tomasz-mrowka-named-head-department-mathematics-1210<p>Tomasz S. Mrowka, the Singer Professor of Mathematics, has been named head of the Department of Mathematics, effective immediately. </p>
<p>“Mathematics holds a unique place at MIT,” Mrowka said. “Much of the community uses it on a daily basis and in an ever-growing and sophisticated manner. The Mathematics department is the nexus of this activity. Its health and strength are crucial for MIT’s future.”<br />
<br />
Mrowka has served as the interim department head since June 2014. Mrowka takes over the role from Michael Sipser, the Barton L. Weller Professor of Mathematics. Sipser was named Dean of the School of Science after serving since last December as interim dean and since 2004 as head of the Department of Mathematics.</p>
<p>“I am delighted that Tom has agreed to be head of mathematics,” said Sipser. “From working with him closely for many of the past 10 years while I was in that role, I know of his deep dedication to the department, to mathematics, and to MIT. He is a stellar mathematician and we are fortunate to have him in this position of leadership.”</p>
<p>Mrowka brings substantial experience as a researcher, educator, and administrator to his role as department head. A 1983 graduate of MIT, he received a PhD from the University of California at Berkeley in 1988 under the direction of Clifford Taubes and Robin Kirby. He taught at Stanford University, Caltech, and Harvard University before returning to MIT in 1996. He served as chair of the Graduate Student Committee from 1999 to 2002 and has chaired the Pure Mathematics Committee since 2004, with a one-year pause in 2009-2010.</p>
<p>Mrowka’s work combines analysis, geometry, and topology, specializing in the use of partial differential equations such as the Yang-Mills equations from particle physics to analyze low-dimensional mathematical objects. Among his results is the discovery (jointly with Robert Gompf of the University of Texas at Austin) of surprising four-dimensional models of space-time topology, going far beyond the expected examples envisaged by Kodaira and others.</p>
<p>In joint work with Peter Kronheimer of Harvard, Mrowka settled many long-standing conjectures, including ones posed by John Milnor on the complexity of knots in three space and another due to Rene Thom on surfaces in four space. Mrowka and Kronheimer also revealed a deep structure underlying the Donaldson invariants of four-dimensional manifolds, which was an avatar of the Seiberg-Witten invariants. In further recent work with Kronheimer, Mrowka used these tools to show that a certain subtle combinatorially-defined knot invariant introduced by Mikhail Khovanov can detect “knottedness.” </p>
<p>Mrowka’s joint work with Kronheimer has been honored by the American Mathematical Society with the 2007 Oswald Veblen Prize in Geometry as well as the 2010 Joseph L. Doob Prize for their monograph<em>, "</em>Monopoles and Three-Manifolds" (Cambridge University Press, 2007). In addition, Mrowka was elected a fellow of the American Academy of Arts and Sciences in 2007 and was named a Guggenheim fellow in 2010 and Fellow of the Radcliffe Institute for Advanced Studies in 2013.</p>
Tomasz Mrowka, the new head of MIT's Department of MathematicsMathematics, School of Science, FacultyTwo MIT seniors and an alumnus named Rhodes Scholars
http://news.mit.edu/2014/three-mit-rhodes-scholars-1123
Elliot Akama-Garren ’15, Anisha Gururaj ’15, and Noam Angrist ’13 are among 32 winners nationwide.Sun, 23 Nov 2014 00:35:08 -0500Nora Delaney | Global Education and Career Developmenthttp://news.mit.edu/2014/three-mit-rhodes-scholars-1123<p>Three MIT nominees — seniors Elliot Akama-Garren and Anisha Gururaj, and alumnus Noam Angrist ’13 — are among the 32 American recipients selected this weekend as Rhodes Scholars. Each will pursue graduate studies next year at Oxford University.</p>
<p>This year’s three Rhodes Scholars from MIT tie the Institute’s 2009 record for the most recipients in a single year. Akama-Garren, Gururaj, and Angrist bring to 49 the number of MIT winners of the prestigious international scholarships since they were first awarded to Americans in 1904.</p>
<p><strong>Elliot Akama-Garren</strong></p>
<p>Elliot Akama-Garren, from Palo Alto, Calif., is an MIT senior majoring in biology. As a Rhodes Scholar, Akama-Garren plans to pursue an MSc in integrated immunology at Oxford before returning to the U.S. to pursue an MD-PhD degree. He hopes to pursue a career in academic medicine — specifically, studying the immune system to find improved treatments for a range of diseases.</p>
<p>Akama-Garren started conducting immunology research at Stanford University as a high school student, ultimately becoming second author on a research paper. During his time at MIT, Akama-Garren has continued work in this field, with research at the Harvard Stem Cell Institute, MIT’s Koch Institute for Integrative Cancer Research, and at Massachusetts General Hospital. In recognition of his work, Akama-Garren was honored with this year’s Thomas J. Bardos Award for Undergraduate Students, awarded by the American Association for Cancer Research.</p>
<p>Since his freshman year, Akama-Garren has been an undergraduate researcher in the laboratory of Tyler Jacks, the David H. Koch Professor of Biology and director of the Koch Institute, where he has studied the potential therapeutic effectiveness of T cells in suppressing lung cancer. This work has resulted in two research papers that are currently under review for publication.</p>
<p>Akama-Garren has served for the last three years as editor-in-chief of the MIT Undergraduate Research Journal. Outside of the laboratory, he is president and co-captain of MIT’s ice hockey team. As team president, Akama-Garren organized a fundraiser game with the Israeli national ice hockey team that attracted more than 800 fans.</p>
<p>“Elliot is a serious thinker who is interested in ideas rather than glory,” says Kim Benard, assistant director of distinguished fellowships in MIT Global Education and Career Development. “In addition to his exemplary academic record, Elliot has been a pivotal member of the MIT hockey team and a dedicated volunteer at Harvard Square Homeless Shelter. He exudes brilliance with compassion.”</p>
<p><strong>Anisha Gururaj</strong></p>
<p>A native of Chesterfield, Mo., Anisha Gururaj is a senior majoring in chemical-biological engineering. As a Rhodes Scholar, she plans to pursue two degrees from Oxford: an MSc in engineering science research, with a focus in bioengineering, and a master’s in public policy. Ultimately, she hopes to build a career developing affordable biomedical devices for use in both the developed and the developing world.</p>
<p>For the past two years, Gururaj has conducted research at MIT’s Little Devices Lab, where she has worked on individualized medical devices that users can assemble themselves. This past summer, she conducted work at the Universidad del Desarollo in Chile to investigate how diagnostic kits created by the Little Devices Lab can be used in rural settings.</p>
<p>Under the supervision of Michael Yaffe, the David H. Koch Professor of Biology and Biological Engineering at MIT, Gururaj co-founded a project to design a low-cost, nonelectric fluid warmer for military trauma victims. During her time at the Institute, Gururaj has also conducted research in the MIT laboratory of Robert Langer, the David H. Koch Institute Professor, and at the National University of Singapore through the Singapore-MIT Alliance for Research and Technology.</p>
<p>Gururaj’s interest in international development has also led her to projects beyond the development of medical devices: She has collaborated with Maiti Nepal, an organization that assists sex-trafficking victims, to expand Nepali girls’ access to K-12 education.</p>
<p>“Anisha Gururaj is an inspiration,” says Rebecca Saxe, an associate professor of cognitive neuroscience and co-chair of MIT’s Presidential Committee on Distinguished Scholarships. “Her accomplishments are pretty remarkable, but what stands out most is how deeply she is committed to translating her knowledge and expertise into practical products and benefits that will make life better for people — whether those people are soldiers on the battlefield, young at-risk women in Nepal, or people living in rural villages with less access to modern health care. She perfectly exemplifies MIT’s mission in the world.”</p>
<p><strong>Noam Angrist</strong></p>
<p>Noam Angrist graduated from MIT in 2013 with a bachelor’s degree in mathematics and economics. He has worked at the intersection of economics and policy, with the goal of reforming education and international aid. As a Rhodes Scholar, Angrist will pursue an MSc in evidence-based social intervention and policy evaluation at Oxford.</p>
<p>Angrist, who hails from Brookline, Mass., was named a Fulbright Scholar to Botswana in 2013. He is currently working in Botswana on educational reform, conducting research on educational outcomes and on successful interventions in public health. He is the co-founder and executive director of Young 1ove, a nonprofit that connects young Africans with life-saving information related to HIV and AIDS.</p>
<p>As an MIT undergraduate, Angrist carried out research related to the Affordable Care Act. He also served as a research analyst for the Jameel Poverty Action Lab under the supervision of Esther Duflo, the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics. While at MIT, Angrist co-founded Amphibious Achievement, an afterschool enrichment program for urban youth that combines academics and aquatic athletics.</p>
<p>“Noam is a force for good in the world,” says John Ochsendorf, the Class of 1942 Professor of Building Technology and Civil and Environmental Engineering and co-chair of MIT’s Presidential Committee on Distinguished Scholarships. “We are delighted that the Rhodes Scholarship will provide him with the opportunity to continue his work at Oxford. Noam has already made numerous important contributions, and the Rhodes Scholarship will greatly amplify his impact.”</p>
Students, Undergraduate, Alumni/ae, Biology, Chemical engineering, Mathematics, Economics, School of Engineering, School of Science, SHASS, Awards, honors and fellowshipsMotion-induced quicksand
http://news.mit.edu/2014/motion-induced-quicksand-1117
MIT granular model explains unusual behavior in sand.Mon, 17 Nov 2014 00:00:02 -0500Jennifer Chu | MIT News Officehttp://news.mit.edu/2014/motion-induced-quicksand-1117<p>From a mechanical perspective, granular materials are stuck between a rock and a fluid place, with behavior resembling neither a solid nor a liquid. Think of sand through an hourglass: As grains funnel through, they appear to flow like water, but once deposited, they form a relatively stable mound, much like a solid.</p>
<p>Ken Kamrin, an assistant professor of mechanical engineering at MIT, studies granular materials, using mathematical models to explain their often-peculiar behavior. Now Kamrin has applied a recent granular model, developed by his group, and shown that it predicts a bizarre phenomenon called “motion-induced quicksand” — a scenario in which the movement of sand in one location changes the character of sand at a distance.</p>
<p>“The moment you start moving sand, it acts like fluid far away,” Kamrin says. “So, for example, if you’re walking in the desert and there’s a sand dune landslide far away, you will start to sink, very slowly. It’s very wacky behavior.”</p>
<p>Researchers have observed this effect in a number of configurations in the lab, including in what’s called an “annular Couette cell” — a geometry resembling the bowl of a food processor, with a rotating ring in its base. In experiments, researchers have filled a Couette cell with sand, and attempted to push a rod horizontally through the sand.</p>
<p>In a stationary Couette cell, the rod will not budge without a significant application of force. If, however, the cell’s inner ring is rotating, the rod will move through the sand with even the slightest push — even where the sand doesn’t appear to be moving.</p>
<p>“It looks like the mechanical behavior of the sand itself has changed because something was moving far away,” Kamrin says. “How the sand responds to stress has changed entirely.”</p>
<p>While others have observed this effect in experiments, there hasn’t previously existed a model to predict such behavior.</p>
<p>In a paper published in the journal <em>Physical Review Letters</em>, Kamrin and his former postdoc David Henann, now an assistant professor at Brown University, applied the granular-flow <a href="http://newsoffice.mit.edu/2012/sand-modeling-0406">model</a> to the problem of motion-induced quicksand, replicating the Couette cell geometry.</p>
<p><br />
<img alt="" src="/sites/mit.edu.newsoffice/files/MIT-Quicksand-02-Embed.gif" style="width: 560px; height: 420px;" /></p>
<p><span style="font-size:11px;"><em>By spinning the turntable at the bottom of the bucket, the turntable "liquifies" the entire granular assembly, even the material very far from it. It has converted a granular solid (a material that has no trouble supporting the weight of the ball) to a granular fluid in which any object denser than the granular pile will sink. The ball is acting like a force probe, showing that the response of the grains has switched from solid to fluid. Graphic: Martin Van Hecke/Leiden</em></span></p>
<p><strong>Modeling spin and creep</strong></p>
<p>Kamrin originally devised the mathematical model to predict scenarios of primary flow, such as the flow field for sand flowing through a chute, or a circular trough. The researchers weren’t sure if the model would also apply to secondary rheology, where motion at a primary location affects movement at a secondary, removed region. </p>
<p>Last summer, Kamrin paid a visit to researchers in France who had carried out earlier experiments on secondary rheology. After some casual discussion, he boarded a train back to his hotel, during which he recalls “having a moment where I thought, ‘I think our model could work.’”</p>
<p>He and Henann ran the model on several configurations of secondary rheology, including the Couette cell, and were able to reproduce the results from previous experiments. In particular, the team observed a direct relationship between the speed of the rotating inner ring and the speed, or “creep,” of the rod through sand: For example, if a constant force is applied to the probe, then spinning the inner ring twice as fast will cause the probe to creep twice as fast — a key observation in laboratory studies</p>
<p>The model is based on the effects of neighboring grains. Where most models would simulate the flow of granular material on a grain-by-grain basis — a computationally laborious task — Kamrin’s continuum model represents the average behavior of a small cube of grains, and builds into the model effects from neighboring cubes. The result is an accurate, and computationally efficient, prediction of granular motion and stress.</p>
<p><strong>Taking the stick out of mud</strong></p>
<p>The mathematical model appears to agree with a general mechanism that researchers have held regarding granular flow, termed a “force chain network.” According to this theory, there exist tiny forces between individual grains that connect the whole of a network. Any perturbation, or movement in the material, can ripple through the network, causing forces between particles to “flicker,” as Kamrin puts it. Such flickering may not be strong enough to move particles, but may weaken bonds between grains, allowing objects to move through the material as if it were liquid.</p>
<p>“Because particles at the wall are connected to particles far away thru the force chain network, by jiggling around over here, you’re making the forces fluctuate thru the material,” Kamrin says. “That’s the picture. But there wasn’t really a general flow model that would reflect this.”</p>
<p>Such forces might partially explain the behavior of quicksand, Kamrin says: While quicksand — a soupy mix of sand and water — may look like a solid, the water in it essentially lubricates the frictional contacts between grains such that when someone steps in it, they sink. In the case of dry granular media, it’s perturbations through the force chain network, not water, that are in essence lubricating the contacts between grains.</p>
<p>“It’s sort of similar, it’s just a different source for what causes the sand to feel lubricated,” Kamrin says.</p>
<p>Kamrin and Henann are now finding ways to package their model into software “so that anybody can download it and predict granular flow.”</p>
<p>“These phenomena are sort of the sticks in the mud that have made granular media an open problem,” Kamrin says. “They’ve made the flow of grains distinct from almost everything we’re used to, like standard solids or regular liquids, because most of those materials don’t have these weird effects.”</p>
<p>This research was funded by the National Science Foundation.</p>
A screenshot of the researcher's quicksand experiment.Mechanical engineering, Industry, National Science Foundation (NSF), Mathematics, Computer modeling, Fluid dynamics, Research, School of ScienceHow do you do math like a girl?
http://news.mit.edu/2014/mit-hosts-math-prize-1015
"Mathletes" show off their talent, passion, and leadership at the sixth annual Math Prize for Girls.Wed, 15 Oct 2014 17:38:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/mit-hosts-math-prize-1015<p>On Sept. 27, a warm Saturday afternoon, 270 students, their families, and volunteers gathered in MIT’s Kresge Auditorium to hear the results of the Math Prize for Girls competition, the world’s largest math prize for female students in grades 7 through 12.</p>
<p>Earlier that morning, the students spent more than two hours working through 20 short-answer problems in algebra, geometry, and trigonometry, vying against some of the most competitive "mathletes" from the U.S. and Canada for tens of thousands of dollars in prize money divided among the top 10 finalists. First prize went to Celine Liang, a junior at Saratoga High School in California.</p>
<p>But the matter of who would take home the top prizes was neither the first nor most important question to settle in the auditorium that afternoon. The more pressing question would be, as Arun Alagappan, co-creator of the Math Prize for Girls and president of the Advantage Testing Foundation asked: “How do you do math like a girl?”</p>
<p>Finding an answer is no small matter, given the glaring gender gaps in math and science in the U.S. Negative stereotypes about women’s ability to excel at math discourage many students from pursuing math, often before they have a chance to discover their talent and passion for it. Alagappan says this gap emerges as early as middle school, “when too many smart, hardworking girls lose their confidence and lose their footing.” </p>
<p>As women advance through high school, college and beyond, they find fewer and fewer female peers and mentors to encourage them to persevere in their pursuit of math — role models who can help them imagine themselves as female mathematician.</p>
<p>Math competitions for middle- and high-school students are no exception to the gender gap: The competitors are predominantly male. It can be dispiriting for female competitors to find themselves in a sea of “boys, boys, and boys,” as Math Prize for Girls alumna Sindy Tan puts it. </p>
<p>Yet these competitions can be an effective way to cultivate a lifelong love of math in students. Anna Ellison, a senior at Newton North High School in Massachusetts and four-time Math Prize for Girls competitor, started participating in math competitions in sixth grade. She didn’t have a particular passion for math to begin with — she joined the math team because, she says, “I thought it was cool.”</p>
<p>She found that she needed to hone her math skills to be competitive, so she began taking extracurricular math classes. But soon she was pursuing math for its own sake, doing self-directed reading online and in textbooks. This year, she’s taking a class in multivariable calculus.</p>
<p>The Math Prize for Girls was founded in 2009 by the Advantage Testing Foundation to make sure students like Ellison have a chance to discover a love of mathematics and be part of a community of peers, mentors, and role models that many aspiring female mathematicians are missing. Each year, competitors are given opportunities to network with their peers and Math Prize for Girls alumnae at events such as a lunch held after the test and a games night hosted by Microsoft the evening before. At each awards ceremony, they hear from women in mathematics who share their work and their experiences, showing the participants different ways to “do math like a girl.”</p>
<p>In this year’s award ceremony, Alagappan contended that the answer to his question — “how to do math like a girl?” — is “brilliantly.” He went on to say that, “Doing math like a girl, doing math like a woman, means approaching problems with imagination and persistence and grit and power.”</p>
<p>MIT professors and industry leaders who spoke after him provided ample evidence for his assertion. Gigliola Staffilani, an MIT mathematics professor and member of the Math Prize for Girls board of advisors, discussed the frustrations and ultimate triumphs of working on complex mathematical theorems. Dina Katabi, an MIT professor of electrical engineering and computer science, showed the audience her new mathematics-based wireless technologies that can track movements behind walls and monitor heart rates remotely. Noelle Faris, president of the Akamai Foundation (one of the event’s sponsors), shared how mathematics developed at MIT was used to create new technologies at Akamai to support internet access. She invited Math Prize for Girls participants to think of themselves as mathematicians and inventors. </p>
<p>Katie Sedlar, an MIT sophomore and Math Prize for Girls alumna, was also among the speakers. Sedlar urged participants to continue as mentors and leaders in mathematics. She emphasized the importance of building mathematics communities that welcome girls and women, especially since they so often face discouragement and lack support. Sedlar believes that one such welcoming community can be found at MIT.</p>
<p>“We love holding the Math Prize at MIT,” she told the audience, “because MIT maintains an outstanding record in supporting and encouraging all its students and faculty. Women as well as men persist in their efforts to solve the hardest problems.”</p>
Math Prize participants work together on a puzzle hunt at Microsoft's game night.School of Science, Mathematics, Students, Awards, honors and fellowships, Contests and academic competitionsGetting metabolism right
http://news.mit.edu/2014/flawed-metabolic-networks-1007
Analysis of 89 models of metabolic processes finds flaws in 44 of them — but suggests corrections.Tue, 07 Oct 2014 10:45:00 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2014/flawed-metabolic-networks-1007<p>Metabolic networks are mathematical models of every possible sequence of chemical reactions available to an organ or organism, and they’re used to design microbes for manufacturing processes or to study disease. Based on both genetic analysis and empirical study, they can take years to assemble.</p>
<p>Unfortunately, a new analytic tool developed at MIT suggests that many of those models may be wrong. Fortunately, the same tool may make it fairly straightforward to repair them.</p>
<p>“They have all these models in this repository hosted at [the University of California at] San Diego,” says Bonnie Berger, a professor of applied mathematics and computer science at MIT and one of the tool’s developers, “and it turns out that many of them were computed with floating-point arithmetic” — an approximate numerical representation that most computer systems use to increase efficiency. “We were able to prove that you need to compute them in exact arithmetic,” Berger says. “When we computed them in exact arithmetic, we found that many of the models that were believed to be realistic don’t produce any growth under any circumstances.”</p>
<p>Berger and colleagues describe their new tool, and the analyses they performed with it, in the latest issue of <em>Nature Communications</em>. First author on the paper is Leonid Chindelevitch, who was a graduate student in Berger’s group when the work was done and is now a postdoc at the Harvard School of Public Health. He and Berger are joined by Aviv Regev, an associate professor of biology at MIT, and Jason Trigg, another of Berger’s former students.</p>
<p>Floating-point arithmetic is kind of like scientific notation for computers. It represents numbers as a decimal multiplied by a base — like 2 or 10 — raised to a particular power. Though it sacrifices some accuracy relative to exact arithmetic, it generally makes up for it with gains in computational efficiency.</p>
<p>Indeed, in order to perform an exact-arithmetic analysis of a data structure as huge and complex as a metabolic network, Berger and Chindelevitch had to find a way to simplify the problem — without sacrificing any precision.</p>
<p><strong>Pruning the network</strong></p>
<p>Metabolic networks, Chindelevitch says, “describe the set of all reactions that are available to a particular organism that we might be interested in. So if we’re interested in yeast or E. coli or the tuberculosis bacterium, this is a way to put together everything we know about what this organism can do to transform some substances into some other substances. Usually it will get nutrients from the environment, and then it will transform them by its own internal mechanisms to produce whatever it is that it wants to produce — ethanol, different cellular components for itself, and so on.”</p>
<p>The network thus represents every sequence of chemical reactions catalyzed by enzymes encoded in an organism’s DNA that could lead from particular nutrients to particular chemical products. Every node of the network represents an intermediary stage in some chain of reactions.</p>
<p>To simplify such networks enough to enable exact arithmetical analysis, Chindelevitch and Berger developed an algorithm that first identifies all the sequences of reactions that, for one reason or another, can’t occur within the context of the model; it then deletes these. Next, it identifies clusters of reactions that always work in concert: Whatever their intermediate products may be, they effectively perform a single reaction. The algorithm then collapses those clusters into a single reaction.</p>
<p>Most crucially, Chindelevitch and Berger were able to mathematically prove that these modifications wouldn’t affect the outcome of the analysis.</p>
<p>“What the exact-arithmetic approach allows you to do is respect the key assumption of the model, which is that at steady state, every metabolite is neither produced in excess nor depleted in excess,” Chindelevitch says. “The production balances the consumption for every substance.”</p>
<p>When Chindelevitch and Berger applied their analysis to 89 metabolic-network models in the San Diego repository, they found that 44 of them contained errors or omissions: If the products of all the reactions in the networks were in equilibrium, the organisms modeled would be unable to grow.</p>
<p><strong>Patching it up</strong></p>
<p>By adapting algorithms used in the field of compressed sensing, however, Chindelevitch and Berger are also able to identify likely locations of network errors.</p>
<p>Compressed sensing exploits the observation that some complex signals — such as audio recordings or digital images — that are computationally intensive to acquire can, upon acquisition, be compressed. That’s because they can be converted into a different mathematical representation that makes them appear much simpler than they did originally. It might be possible, for example, to represent an audio signal that initially consists of 44,000 samples per second of its duration as the <a href="http://newsoffice.mit.edu/2009/explained-fourier">weighted sum</a> of a much smaller number of its constituent frequencies.</p>
<p>Compressed sensing performs the initial sampling in a clever way that allows it to build up the simpler representation from scratch, without having to pass through the more complex representation first. In the same way that compressed sensing can decompose an audio signal into the constituent frequencies with the heaviest weights, Chindelevitch and Berger’s algorithm can isolate just those links in a metabolic network that contribute most to its chemical imbalance.</p>
<p>“We’re hoping that this work will provide an impetus to reanalyze a lot of the existing metabolic-network model reconstructions and hopefully spur some collaborations where we actually perform this analysis and suggest corrections to the model before it is published,” Chindelevitch says.</p>
<p>“This is not an area where one would expect there to be a problem,” says Desmond Lun, chair of the Department of Computer Science at Rutgers University, who studies computational biology. “I think [the MIT researchers’ work] will change people’s attitudes in the sense that it raises an issue that most people would have thought was not an issue, and I think it will make us a lot more careful.”</p>
<p>“Computers operate with limited precision because there are only so many digits that you can store — even though, I must say, they store a lot of digits,” Lun explains. “Through software, you can be more or less careful about how much precision you lose in that way. There are very, very good packages out there that try to minimize that problem. And mostly, I would have thought, and I think most people would have thought, that that would be sufficient for these metabolic models.”</p>
<p>Errors in the models may have gone unnoticed because analyses performed on them often comported well with empirical evidence. But “those floating-point errors vary from package to package,” Lun says. “Certainly, it would be very concerning to find that because somebody used this software package, they got these great results, and then if I used a different software package, I would not.”</p>
Compressed sensing, Computational biology, Metabolism, Synthetic biology, School of Engineering, School of Science, Computer Science and Artificial Intelligence Laboratory (CSAIL), Biology, Electrical Engineering & Computer Science (eecs), Mathematics, Research, Algorithms, Computer science and technologyMore than a prize
http://news.mit.edu/2014/math-prize-for-girls-offers-inspiration-mentorship-0923
Math Prize for Girls offers inspiration and mentorship to participants on MIT’s campus.Tue, 23 Sep 2014 17:40:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/math-prize-for-girls-offers-inspiration-mentorship-0923<p>Bright and early on Saturday, Sept. 27, 2014, more than 200 mathletes will converge on the MIT campus to compete in the world’s largest mathematics competition for young women in high school, the Advantage Testing Foundation’s Math Prize for Girls.</p>
<p>Joining them will be Sindy Tan, an undergraduate at Harvard University and a volunteer for the <a href="http://mathprize.atfoundation.org/index" target="_blank">Math Prize for Girls</a>. Tan herself is a veteran of math competitions, having participated in her first competition in the eighth grade and continuing all through high school. Math competitions were central to Tan’s growing love of math. They gave her the chance to build a tool box of powerful problem-solving concepts and to use them in creative ways. She was excited to meet other talented people who also appreciated the beauty of math and who were eager to share their own imaginative ways of solving problems.</p>
<p>But when Tan looked around at her peers on the competition circuit, she didn’t find very many other women and girls. There was nothing to counter the sense of being surrounded by “boys, boys, and boys,” Tan says.</p>
<p>That is, until Tan was invited to compete in the Math Prize for Girls for the first time in 2011 and again in 2013. She found a community of girls and women who loved math and encouraged each other to pursue it. Now she is back to help other girls have the same inspiring experience she did.</p>
<p>The Math Prize for Girls was established in 2009 by Ravi Boppana, the co-director of mathematics at Advantage Testing, with the aim of bringing math-minded girls together, inspiring them to pursue their love of mathematics, and encouraging them to become mentors to others. After New York University hosted the competition for its first two years, the Math Prize for Girls has been held at MIT since 2011. Two professors from the MIT Department of Mathematics, Gigliola Staffilani and Michael Sipser — who is also dean of the School of Science — serve on the competition’s board of advisors.</p>
<p>“I am impressed by the achievements and enthusiasm of the Math Prize for Girls competitors,” says Sipser. “I am delighted that we have the opportunity to support the girls in their growth as problem solvers and mentors. I look forward to seeing what they accomplish in the future — and hope that many of them will come to MIT as students or faculty someday.”</p>
<p>In many ways, the Math Prize for Girls is not very different from other high school math competitions. Participants, who qualify by taking the American Mathematics Competition exam, must complete 20 short-answer problems in geometry, algebra, and trigonometry in 150 minutes. The exams are then reviewed by a panel of judges, who award a cash prizes to the top-scoring participants — in this case, $25,000 for first place, $10,000 for second place, and $5,000 for third place. </p>
<p>But as the girls enjoy Games Night at Microsoft the evening before the competition, and while they wait nervously for their scores after they take the test, the girls will have an opportunity to meet new like-minded people, see old friends, and — of course — talk about math. They will begin to build a network of peers that will last into their college years and beyond.</p>
<p>Melody Guan, another Harvard undergraduate and Math Prize for Girls alumna believes that networking and mentorship are important tools for encouraging girls and women to keep pursuing their love of math.</p>
<p>“Math remains a male-dominated field,” says Guan, “so being a female mathlete can be a lonesome and isolating experience, which can turn girls off to math.”</p>
<p>However, finding a network of other women and girls who share a passion for mathematics can be a powerful experience — one that helps many girls pursue their interests in mathematics and other science fields in the long run. Guan thinks that this is why the community of girls brought together by the Math Prize for Girls is so important.</p>
<p>“Indeed, while there is an increasing number of successful female mathematicians who can serve as fantastic role models for math-loving girls — the most recent example being Fields Medalist Maryam Mirzahkani — they can be seen as the exception rather than the rule,” says Guan. “And in a way, there is nothing quite as empowering as finding yourself in a huge auditorium surrounded by other girls who love and rock math.”</p>
<p>Where Tan and Guan are concerned, the Math Prize for Girls has succeeded in its mission of inspiring girls to pursue math and science and in building a network of peers and mentors. Tan, still in her first year at Harvard, hasn’t declared her major yet, but is considering math and is a co-organizer of the <a href="http://hmmt.mit.edu/" target="_blank">Harvard-MIT Math Tournament</a>, a semi-annual competition for high school and middle school students. Guan, in her third year at Harvard, is studying chemistry, physics, and statistics, and is an undergraduate researcher at the Harvard Stem Cell Institute. Guan assists at math camps, served as a board member at the Harvard-MIT Math Tournament, has designed and taught high school math and science classes through the MIT Educational Studies Program, and has been a course assistant to her fellow students at Harvard. They will both be volunteering at the Math Prize for Girl on Saturday.</p>
<p>To learn more about how you can support the Math Prize for Girls, please visit their <a href="http://mathprize.atfoundation.org/index" target="_blank">their website</a>.</p>
Contests and academic competitions, Mathematics, STEM education, Diversity, Women in STEM, School of Science, Education, teaching, academics, WomenMacArthur confers “genius” awards for playful math and practical art
http://news.mit.edu/2014/macarthur-confers-genius-awards-jacob-lurie-rick-lowe-ai-jen-poo-0919
Fri, 19 Sep 2014 15:57:01 -0400Nicole Estvanik Taylor | MIT Spectrumhttp://news.mit.edu/2014/macarthur-confers-genius-awards-jacob-lurie-rick-lowe-ai-jen-poo-0919<p>A mathematician and an artist with MIT connections were among the 21 lucky recipients a few weeks ago of a surprise phone call from the MacArthur Foundation. They had been selected, through a secret nomination process, as MacArthur “Genius” Fellows — receiving $625K with no strings attached, plus a rush of prestige and validation when the official announcement came on September 17.</p>
<p>Jacob Lurie PhD ’04, a former MIT associate professor who is now on the mathematics faculty at Harvard University, was recognized for creating a conceptual foundation for derived algebraic geometry. “At an oversimplified level,” the MacArthur website helpfully supplies, “he is transforming algebraic geometry to derived algebraic geometry — replacing the role of sets by topological spaces — making it applicable to other areas in new ways.” Lurie is now training young theorists in his mathematical vision, and he also hopes to inspire a sense of excitement about math in high school students and college undergraduates.</p>
<p>“Mathematics is a giant playground filled with all kinds of toys that the human mind can play with,” Lurie says in a video on his MacArthur <a href="http://www.macfound.org/fellows/921/" target="_blank" title=" Jacob Lurie">profile</a>, “but many of these toys have very long operating manuals.”</p>
<p>Another honoree, Rick Lowe, a 2014 Mel King Community Fellow at MIT’s Community Innovators Lab, received the MacArthur not for his original vocation as a painter, but for his two decades improving communities through public art. In 1993, he founded <a href="http://projectrowhouses.org/" target="_blank" title="Project Row Houses">Project Row Houses</a>, which transformed a block and a half of run-down buildings in Houston’s historically significant and culturally charged Third Ward neighborhood into an arts venue and community center. Lowe has also spearheaded arts-driven redevelopment projects in North Dallas, New Orleans, and Los Angeles.</p>
<p>See Lowe’s MacArthur <a href="http://www.macfound.org/fellows/920/" target="_blank" title=" Rick Lowe">profile</a>, and listen to a <a href="http://www.kera.org/2013/11/20/energizing-neighborhoods-through-art/" target="_blank" title=" Rick Lowe">public radio interview</a> in which he describes his vision for energizing urban neighborhoods through art.</p>
<p>A third MacArthur grantee this year, <a href="http://www.macfound.org/fellows/924/" target="_blank">Ai-jen Poo</a>, also has a history with MIT: She was a fellow at the Community Innovators Lab in 2013. As director of the <a href="http://www.domesticworkers.org/" target="_blank">National Domestic Workers Alliance</a>, she is helping to transform the landscape of working conditions and labor standards for the estimated 1–2 million people employed in the United States as housekeepers, nannies, and caregivers for the elderly or disabled.</p>
<div></div>
Jacob Lurie and Rick LoweAwards, honors and fellowships, Alumni/ae, Community Innovator Lab, Mathematics, School of Science, School of Architecture + PlanningFluid mechanics suggests alternative to quantum orthodoxy
http://news.mit.edu/2014/fluid-systems-quantum-mechanics-0912
New math explains dynamics of fluid systems that mimic many peculiarities of quantum mechanics.Fri, 12 Sep 2014 00:00:00 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2014/fluid-systems-quantum-mechanics-0912<p>The central mystery of quantum mechanics is that small chunks of matter sometimes seem to behave like particles, sometimes like waves. For most of the past century, the prevailing explanation of this conundrum has been what’s called the “Copenhagen interpretation” — which holds that, in some sense, a single particle really is a wave, smeared out across the universe, that collapses into a determinate location only when observed.</p>
<p>But some founders of quantum physics — notably Louis de Broglie — championed an alternative interpretation, known as “pilot-wave theory,” which posits that quantum particles are borne along on some type of wave. According to pilot-wave theory, the particles have definite trajectories, but because of the pilot wave’s influence, they still exhibit wavelike statistics.</p>
<p>John Bush, a professor of applied mathematics at MIT, believes that pilot-wave theory deserves a second look. That’s because Yves Couder, Emmanuel Fort, and colleagues at the University of Paris Diderot have recently discovered a macroscopic pilot-wave system whose statistical behavior, in certain circumstances, recalls that of quantum systems.</p>
<p>Couder and Fort’s system consists of a bath of fluid vibrating at a rate just below the threshold at which waves would start to form on its surface. A droplet of the same fluid is released above the bath; where it strikes the surface, it causes waves to radiate outward. The droplet then begins moving across the bath, propelled by the very waves it creates.</p>
<p>“This system is undoubtedly quantitatively different from quantum mechanics,” Bush says. “It’s also qualitatively different: There are some features of quantum mechanics that we can’t capture, some features of this system that we know aren’t present in quantum mechanics. But are they philosophically distinct?”</p>
<p><strong>Tracking trajectories</strong></p>
<p>Bush believes that the Copenhagen interpretation sidesteps the technical challenge of calculating particles’ trajectories by denying that they exist. “The key question is whether a real quantum dynamics, of the general form suggested by de Broglie and the walking drops, might underlie quantum statistics,” he says. “While undoubtedly complex, it would replace the philosophical vagaries of quantum mechanics with a concrete dynamical theory.”</p>
<p>Last year, Bush and one of his students — Jan Molacek, now at the Max Planck Institute for Dynamics and Self-Organization — did for their system what the quantum pioneers couldn’t do for theirs: They derived an equation relating the dynamics of the pilot waves to the particles’ trajectories.</p>
<p>In their work, Bush and Molacek had two advantages over the quantum pioneers, Bush says. First, in the fluidic system, both the bouncing droplet and its guiding wave are plainly visible. If the droplet passes through a slit in a barrier — as it does in the re-creation of a canonical quantum experiment — the researchers can accurately determine its location. The only way to perform a measurement on an atomic-scale particle is to strike it with another particle, which changes its velocity.</p>
<p>The second advantage is the relatively recent development of chaos theory. <a href="http://www.technologyreview.com/article/422809/when-the-butterfly-effect-took-flight/">Pioneered</a> by MIT’s Edward Lorenz in the 1960s, chaos theory holds that many macroscopic physical systems are so sensitive to initial conditions that, even though they can be described by a deterministic theory, they evolve in unpredictable ways. A weather-system model, for instance, might yield entirely different results if the wind speed at a particular location at a particular time is 10.01 mph or 10.02 mph.</p>
<p>The fluidic pilot-wave system is also chaotic. It’s impossible to measure a bouncing droplet’s position accurately enough to predict its trajectory very far into the future. But in a recent series of papers, Bush, MIT professor of applied mathematics Ruben Rosales, and graduate students Anand Oza and Dan Harris applied their pilot-wave theory to show how chaotic pilot-wave dynamics leads to the quantumlike statistics observed in their experiments.</p>
<p><strong>What’s real?</strong></p>
<p>In a review article appearing in the <em>Annual Review of Fluid Mechanics</em>, Bush explores the connection between Couder’s fluidic system and the quantum pilot-wave theories proposed by de Broglie and others.</p>
<p>The Copenhagen interpretation is essentially the assertion that in the quantum realm, there is no description deeper than the statistical one. When a measurement is made on a quantum particle, and the wave form collapses, the determinate state that the particle assumes is totally random. According to the Copenhagen interpretation, the statistics don’t just describe the reality; they are the reality.</p>
<p>But despite the ascendancy of the Copenhagen interpretation, the intuition that physical objects, no matter how small, can be in only one location at a time has been difficult for physicists to shake. Albert Einstein, who famously doubted that God plays dice with the universe, worked for a time on what he called a “ghost wave” theory of quantum mechanics, thought to be an elaboration of de Broglie’s theory. In his 1976 Nobel Prize lecture, Murray Gell-Mann declared that Niels Bohr, the chief exponent of the Copenhagen interpretation, “brainwashed an entire generation of physicists into believing that the problem had been solved.” John Bell, the Irish physicist whose famous theorem is often mistakenly taken to repudiate all “hidden-variable” accounts of quantum mechanics, was, in fact, himself a proponent of pilot-wave theory. “It is a great mystery to me that it was so soundly ignored,” he said.</p>
<p>Then there’s David Griffiths, a physicist whose “Introduction to Quantum Mechanics” is standard in the field. In that book’s afterword, Griffiths says that the Copenhagen interpretation “has stood the test of time and emerged unscathed from every experimental challenge.” Nonetheless, he concludes, “It is entirely possible that future generations will look back, from the vantage point of a more sophisticated theory, and wonder how we could have been so gullible.”</p>
<p>“The work of Yves Couder and the related work of John Bush … provides the possibility of understanding previously incomprehensible quantum phenomena, involving 'wave-particle duality,' in purely classical terms,” says Keith Moffatt, a professor emeritus of mathematical physics at Cambridge University. “I think the work is brilliant, one of the most exciting developments in fluid mechanics of the current century.”</p>
Copenhagen interpretation, Pilot-wave theory, Quantum mechanics, Mathematics, School of ScienceFive professors join the School of Science this fall
http://news.mit.edu/2014/five-professors-join-school-science-fall
New faculty members will join the departments of Chemistry, Mathematics, and Earth, Atmospheric and Planetary Sciences.
Tue, 09 Sep 2014 11:30:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/five-professors-join-school-science-fall<p>Five new professors have joined the School of Science this fall in the departments of Chemistry, Mathematics, and Earth, Atmospheric and Planetary Sciences. Their research interests span a range of topics, including the genetics of ancient microbes, the chemistry of cell membrane proteins and intercellular interactions, the development of new methods of controlling catalyzed reactions, and symplectic and contact geometry.</p>
<p><strong>Gregory Fournier</strong></p>
<p>Fournier joins the Department of Earth, Atmospheric and Planetary Sciences as an assistant professor of geobiology. His research integrates phylogenetics and horizontal gene transfer (HGT) with studies of microbial evolution, geochemistry, and planetary history. Specific areas of his research include: HGT- and genome-based calibration of molecular clock models of microbial evolution; ancestral reconstruction of ancient proteins and metabolisms; the biogeochemical impact of HGT and microbial metabolism evolution; the role of partial HGT in the complex ancestry of organismal lineages; and using HGT events to identify novel antibiotic drug targets for protozoan diseases. Fournier received his PhD in genetics and genomics from the University of Connecticut and his bachelor's in genetics, cell and developmental biology from Dartmouth College.</p>
<p><strong>Mei Hong</strong></p>
<p>Hong joins the Department of Chemistry as a professor this fall. Her research seeks to elucidate the structure, dynamics, and mechanism of membrane proteins and other biological macromolecules using advanced multidimensional solid-state NMR spectroscopy. Phospholipid membranes and proteins embedded in them are universal components of cells and play key roles in many cellular functions. Hong is particularly interested in how the structure and dynamics of membrane peptides and proteins underlie their abilities to conduct ions across the lipid bilayer, catalyze fusion of virus envelopes and cell membranes, and disrupt microbial cell membranes during immune defense. She also studies the structure of the polysaccharide-rich plant cell walls in order to understand how cellulose and matrix polysaccharides form the 3-D architecture that both provides mechanical strength to plant cells and allows plant cells to grow. Hong received her bachelor's in 1992 from Mount Holyoke College and her PhD in 1996 from the University of California at Berkeley. After a National Institutes of Health postdoc fellowship at MIT, she became a professor at the University of Massachusetts at Amherst in 1997 and then at Iowa State University in 1999. She is a fellow of the American Association for the Advancement of Science and has won numerous awards and honors, such as the 2003 Pure Chemistry Award from the American Chemical Society and the 2010 Founders Medal from the International Council on Magnetic Resonance in Biological Systems.</p>
<p><strong>Emmy Murphy</strong></p>
<p>Murphy, an assistant professor of mathematics, first came to MIT as a CLE Moore Instructor of Mathematics in 2012. She works in symplectic and contact geometry, specifically in higher dimensions. Her work primarily focuses on construction and classification of geometric objects through symplectic flexibility. After earning her bachelor's in mathematics in 2007 at the University of Nevada at Reno, she completed her PhD in 2012 under Yakov Eliashberg at Stanford University. Her thesis defined a class of Legendrian submanifolds for which the h-principle holds. This has applications to a partial classification of Stein manifolds up to deformation. Since coming to MIT, there have been two major developments in the field by Murphy and her co-authors. The first of these gives constructions of irregular Lagrangian submanifolds, including closed Lagrangians which have no interpretation in mirror symmetry, and demonstrating that exact Lagrangian immersions do not conform to the philosophy of the Arnol'd conjecture. The second development shows that every smooth manifold admits a contact structure, except for those which obviously cannot for homological reasons. It also gives a partial classification of contact structures by extending the notion of overtwistedness to high dimensions. These address long-standing problems in contact, symplectic, and complex geometry, contributing to a fundamental perspective shift in the understanding of high dimensional contact and symplectic manifolds.</p>
<p><strong>Alex Shalek</strong></p>
<p>Shalek joins the Department of Chemistry as an assistant professor with joint appointments to the Institute for Medical Engineering and Science (IMES) at MIT and the Ragon Institute of MGH, MIT, and Harvard. His research is directed towards the development and application of new technologies that facilitate understanding of how cells collectively perform systems-level functions in healthy and diseased states. With respect to technology development, the Shalek lab leverages recent advances in nanotechnology and chemical biology to establish a host of core, cross-disciplinary platforms that collectively enable them to extensively profile and precisely control cells and their interactions within the context of complex systems. With respect to biological applications, the group focuses on how cellular heterogeneity and cell-to-cell communication drive ensemble-level decision-making in the immune system, with an emphasis on “two-body” interaction (such as host cell-virus interactions, innate immune control of adaptive immunity, tumor infiltration by immune cells). His goal is to not only provide broadly applicable experimental tools, but also help transform the way in which we think about single cells, cell-cell interactions, diseased cellular states, and therapeutics, to create a new paradigm for understanding and designing systems-level cellular behaviors in multicellular organisms. After Shalek received his bachelor's in chemical physics from Columbia University in 2004, he completed his PhD at Harvard University in 2011, where he remained as a postdoc fellow.</p>
<p><strong>Jeffrey Van Humbeck</strong></p>
<p>Van Humbeck joins the Department of Chemistry as an assistant professor. His laboratory will develop new methods for controlling catalytic reactions, and the structure of organic materials. By incorporating catalysts within restrictive supramolecular volumes, size-selective oligomerization will be pursued in the context of energy applications (such as biofuels upgrading) and medicinal chemistry (such as polyketide synthesis). Further investigations in the area of catalysis will probe the effect of including ionically charged elements in traditional catalyst structures, with aims of improving both efficiency and selectivity in new reactions. Ion pairing — as a means of structural control — has been explored to a much greater extent in polymers, where the typical units of charge result from proton transfer. As an alternative, the inclusion of inherently charged units that lack protons will be pursued, for both functional and structural organic materials. Additionally, the development of charge by electron transfer between redox active centers will be investigated as an avenue to produce responsive materials. Van Humbeck comes to MIT from a postdoc fellowship at University of California at Berkeley. He completed his bachelor's at the University of Calgary in 2005 and his PhD at Princeton University in 2011.</p>
School of Science, Faculty, Earth and atmospheric sciences, Mathematics, ChemistrySchool of Science announces winners of Teaching Prizes for Graduate and Undergraduate Education
http://news.mit.edu/2014/school-science-teaching-prizes
Rick Danheiser and Bjorn Poonen are lauded for their outstanding teaching.Wed, 27 Aug 2014 15:00:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/school-science-teaching-prizes<p>The School of Science recently announced the winners of its 2014 Teaching Prizes for Graduate and Undergraduate Education. The prizes are awarded annually to School of Science faculty members who demonstrate excellence in teaching in their courses for that year. Winners are chosen from nominations by their students or colleagues.</p>
<p><a href="http://chemistry.mit.edu/people/danheiser-rick">Rick Danheiser</a>, the A. C. Cope Professor of Chemistry, was awarded the prize for graduate education for his class 5.511 (Principles of Chemical Science). Danheiser’s nominators not only considered him to be an inspiring teaching and a dedicated mentor, but also a “paragon of clarity, conciseness, and precision” whose lecture notes continue to be an invaluable resource for many of his students long after the course is over.</p>
<p><a href="http://math.mit.edu/directory/profile.php?pid=213">Bjorn Poonen</a>, the C. E. Shannon (1940) Professor in Mathematics, was awarded the undergraduate education prize for his class, 18.03 (Differential Equations). Poonen’s nominators repeatedly remarked on his dedication to his students' success and well-being, both inside and outside the classroom, as well as his humorous approach to teaching and passion for the subject.</p>
<p>The School of Science welcomes Teaching Prize nominations for its faculty during the spring semester each academic year. For more information please visit the School’s <a href="http://science.mit.edu/">website</a>.</p>
Awards, honors and fellowships, Chemistry, Mathematics, School of Science, Education, teaching, academics, FacultyOvercoming imperfections
http://news.mit.edu/2014/profile-student-leon-dimas-0702
By looking to nature, PhD student Leon Dimas 3-D prints materials that resist flaws and fractures.Wed, 02 Jul 2014 00:00:03 -0400Zach Wener-Fligner | MIT News correspondenthttp://news.mit.edu/2014/profile-student-leon-dimas-0702<p>MIT graduate student Leon Dimas is no stranger to resilience: At 18, as a rising soccer star, the long-armed goalkeeper was a promising prospect who played for the youth academy of Rosenborg BK, a top-ranked Norwegian soccer club. He was set, it seemed, on a path that would allow him to pursue a professional career playing the game that was his first love.</p>
<p>But when Dimas suffered nagging damage to a shoulder tendon, his professional prospects dimmed. Over the course of the next year, he made the decision to abandon professional soccer for good. “Once that dream broke, you wonder if you can get these kinds of feelings again,” Dimas says, “feelings of accomplishment and that someone believes in you.”</p>
<p>It’s fair to say that Dimas, now a doctoral student in MIT’s Department of Civil and Environmental Engineering, has bounced back. Fittingly, he is now working on creating new materials that have resilience of their own — by borrowing from the oldest blueprint around.</p>
<p>“The main idea is to look into nature,” Dimas says, “specifically, investigating mineralized composites and trying to understand why they perform so well.”</p>
<p>Biomaterials such as bone and nacre (also known as mother-of-pearl) remain robust even in the presence of cracks, defects, or other flaws. Such materials are composed of brittle minerals and soft proteins — ingredients that are weak, but exhibit strength when combined in hierarchical geometries. In bone, for example, the brittle mineral apatite and the soft protein collagen are arranged in patterns that yield a strong and tough composite.</p>
<p>In a series of interrelated papers, the most recent of which was published last year in <em>Advanced Functional Materials</em>, Dimas and other researchers — including his advisor, Professor Markus Buehler, head of MIT’s Department of Civil and Environmental Engineering — created models that predicted the fracture response, fracture resistance, and durability of synthetic materials that arranged their ingredients in various natural and synthetic geometries. In the most recent paper, the researchers showed that they could efficiently 3-D print such materials, and that their model accurately predicted the resulting material’s properties.</p>
<p>Such research could eventually lead to new “metamaterials” that combine nature’s designs with human engineering — resulting in cars, or whole buildings, constructed from superstrong synthetic skeletons.</p>
<p>“The limit is having a material with flaws that behaves as though it is pristine,” Dimas says. “With an improved understanding of how these cracks act and how we can mitigate their consequences, we can shoot for more high-performing and more lightweight structures — using less material, more efficiently.”</p>
<p><strong>Athletics to academics</strong></p>
<p>Dimas’ favorite subject in school was always mathematics, but, he says, “Without the pressure of my parents I doubt that I would have pursued it as much as I have done now. I wanted to play soccer. I didn’t want to do my homework.”</p>
<p>His soccer career had humble beginnings: His older brother wanted someone to shoot the ball at, so Dimas found a pair of leather gloves and took on the role of goalkeeper. “From when I could walk I was probably playing close to every day,” he says.</p>
<p>The family was living in New Jersey at the time, while Dimas’ father completed his PhD in philosophy at Princeton University. After finishing, they moved to England, where Dimas, at age 8, began to get serious about soccer. He was allowed to try out for an elite English youth academy, and although his family moved to Norway shortly thereafter, he had caught the bug. If he didn’t have team practice, he would play on his own, pounding a ball into a net or kicking it off a concrete wall over and over — taking advantage of the random ricochet provided by the wall’s imperfections, forcing him to practice his footwork.</p>
<p>His family made sure school remained a priority. During his last year of high school, when Dimas was preparing for exams by taking practice tests, his parents were unimpressed by his progress. “My grades were not great,” he says. “And my parents said, ‘All right: You’re going to go into this room right now and you’re going to stay. You can play your games, but you’re not going to practice.’”</p>
<p>Dimas skipped practice for nearly a month, and his preparation worked: He aced his tests and matriculated in a five-year master’s program in structural engineering at Norwegian University of Science and Technology (NTNU), still juggling soccer alongside school. “It’s actually quite unusual to pursue an education at the same time as you’re pursuing your [soccer] career,” he says. “It kind of meant that I’d be missing half my lectures because we’d have practice in the morning. Sometimes we’d have two practices a day.”</p>
<p>Then, in the fourth year of his program, after veering from the professional soccer trajectory, Dimas took a year abroad to study at MIT. “I came here in August and by late September I was determined I wanted to stay,” he says. “In October I was already starting to apply. So it didn’t take me long to decide that this was the place that I really wanted to be.”</p>
<p>What particularly struck Dimas was the hands-on, personal nature of learning at MIT. His master’s program at NTNU was “more of an engineering training school, while [at MIT] it seems like more of a scientific exploration,” he says. “It’s a very motivating thing when you have these very renowned professors that are actually interested in discussing things with you. It makes you want to contribute and it makes you feel like you can contribute.”</p>
<p>After impressing faculty during his time at MIT, the good news came. “There was a Friday afternoon in March that I was emailed that I was going to be accepted,” he says. “Later I got the letter of acceptance, and I have yet to open it. And I’m kind of saving it for a bad day, because that was big. That really meant a lot to me.”</p>
<p><strong>Teaching through thinking</strong></p>
<p>When Dimas came to MIT, he soon realized that an important activity was missing: At NTNU, he had been a teaching assistant, which he loved. “My TA sessions were the highlight of my week,” he says. “You get to accompany your colleagues on a journey from not understanding to understanding. And you know that you have been able to help them through this journey.”</p>
<p>Dimas wanted to continue teaching, but with a different focus. In 2012, he founded MITxplore with two other MIT graduate students and funding from the MIT Public Service Center. The organization, which is run entirely by MIT students, holds afterschool programs for 50 fifth-graders in three different locations in Cambridge and Boston. The goal is to encourage learning in math through experimentation and exploration.</p>
<p>“I don’t care too much if [the students] learn a specific concept or understand a specific engineering phenomenon,” Dimas says. “I just want them to think, and become confident that they can put themselves on the path from not understanding to understanding. Understanding is the most empowering thing.”</p>
<p>They often explore difficult concepts using simple materials — such as an exercise that involves squeezing Play-Doh through a nozzle that can vary in size. The students note that the narrower the nozzle diameter, the longer the Play-Doh string.</p>
<p>Then the instructors pose a question: What if we could make the nozzle as small as we wanted? Could we make the Play-Doh string as long as we wanted? “And just like that, all of a sudden they’re exploring this concept of infinity,” Dimas says. “And that is, I’d say, a pretty complex concept for a 10-year-old to understand.”</p>
Leon DimasStudents, Profile, Graduate, postdoctoral, Civil and environmental engineering, Bioengineering and biotechnology, Materials science, Education, teaching, academics, K-12 education, Mathematics, Volunteering, outreach, public service, ResearchMathematical patchwork
http://news.mit.edu/2014/profile-mathematician-alice-guionnet-0627
Alice Guionnet, an authority on random matrix theory, aims to make sense of huge data sets.Fri, 27 Jun 2014 00:00:02 -0400Helen Knight | MIT News Officehttp://news.mit.edu/2014/profile-mathematician-alice-guionnet-0627<p>From the increasing information transmitted through telecommunications systems to that analyzed by financial institutions or gathered by search engines and social networks, so-called “big data” is becoming a huge feature of modern life.</p>
<p>But to analyze all of this incoming data, we need to be able to separate the important information from the surrounding noise. This requires the use of increasingly sophisticated techniques.</p>
<p>Alice Guionnet, a professor of mathematics at MIT, investigates methods to make sense of huge data sets, to find the hidden correlations between apparently random pieces of information, their typical behavior, and random fluctuations. “I consider things called matrices, where you have an array of data,” Guionnet says. “So you take some data at random, put it in a big array, and then try to understand how to analyze it, for example to subtract the noise.”</p>
<p>The field of random matrix theory, as it is known, has grown rapidly over the last 10 years, thanks to the huge rise in the amount of data we produce. The theory is now used in statistics, finance, and telecommunications, as well as in biology to model connections between neurons in the brain, and in physics to simulate the radiation frequencies absorbed and emitted by heavy atoms.</p>
<p><strong>Mathematics as patchwork</strong></p>
<p>A world-leading researcher in probability, Guionnet has made important theoretical contributions to random matrix theory. In particular, she has made recent advances in understanding large deviations — the probability of finding unlikely events or unusual behavior within the array of data — and in connecting the theory with that of topological expansion, in which random matrices are used to help solve combinatorial questions.</p>
<p>“It’s a bit like when you make a patchwork quilt,” Guionnet says. “So you have all of your pieces of patchwork, and then you go to sew them together so that they make a nice pillow with no holes, and you have many possibilities for how to lay them out,” she says.</p>
<p>Random matrices can be used to calculate the number of ways in which this “patchwork” can be sewn together, Guionnet says. She also considers several of these random arrays simultaneously, to help solve problems in the field of operator algebra.</p>
<p>Guionnet was born in Paris. She completed her master’s degree at the Ecole Normale Superieure Paris in 1993, and then moved to the Universite Paris Sud to undertake her PhD. The focus of her PhD was the statistical mechanics of disordered systems, a branch of mathematical physics in which the world around us is modeled down to the level of microscopic particles. In this way, researchers attempt to determine how microscopic interactions affect activity at the macroscopic level.</p>
<p>In particular, Guionnet was interested in objects called spin glasses — disordered magnetic materials that are similar to real glass, in that they appear to be stationary, but which are actually moving, albeit at an incredibly slow rate. “If you looked at the windows of your house millions of years from now, they may be shifting downward as a result of gravity,” she says. “I was attempting to analyze the dynamics of these kinds of systems.”</p>
<p>Before she had completed her PhD, Guionnet was offered a position within the French National Center for Scientific Research (CNRS), and moved to Ecole Normale Superieure (ENS) Lyon, where she continued to focus on the spin glass model, before branching out into random matrices. “I initially wanted to work in applied mathematics,” Guionnet says. “But as I started to consider questions in random matrix theory, I moved into purer and purer mathematics.”</p>
<p>While at ENS Lyon, she was made a director of research for CNRS, and was given the opportunity to build her own team of top researchers in probability theory.</p>
<p><strong>Making connections</strong></p>
<p>She moved to MIT in 2012, where she continues her work in random matrix theory. In the same year, Guionnet was chosen as one of 21 mathematicians, theoretical physicists, and theoretical computer scientists named as Simons Investigators. Awarded by the Simons Foundation, a private organization that aims to advance research in math and the basic sciences, Simons Investigators each receive $100,000 annually to support their work.</p>
<p>“What I like about my work is that it crosses over into different fields — probability theory, operator algebra, and random matrices — and I’m trying to advance these three theories at the same time,” Guionnet says. “These different fields are all merging and connecting with each other, and that is what I try to understand in my work.”</p>
<p>The opportunity to work with people from different mathematical fields, and to learn new ideas from them, is one of the things Guionnet loves most about the subject. “When you work with people from different fields you begin to make new connections, and get a new point of view on the object you are studying, so it’s kind of exciting,” she says.</p>
<p>What’s more, the math itself is always evolving and progressing, she says: “Mathematics is beautiful.”</p>
Mathematics, Profile, Faculty, School of Science, Data, Big data, ProbabilityExplained: How does a soccer ball swerve?
http://news.mit.edu/2014/explained-how-does-soccer-ball-swerve-0617
The smoothness of a ball’s surface — in addition to playing technique — is a critical factor.Tue, 17 Jun 2014 00:00:02 -0400Peter Dizikes | MIT News Officehttp://news.mit.edu/2014/explained-how-does-soccer-ball-swerve-0617<p>It happens every four years: The World Cup begins and some of the world’s most skilled players carefully line up free kicks, take aim — and shoot way over the goal.</p>
<p>The players are all trying to bend the ball into a top corner of the goal, often over a wall of defensive players and away from the reach of a lunging goalkeeper. Yet when such shots go awry in the World Cup, a blame game usually sets in. Players, fans, and pundits all suggest that the new official tournament ball, introduced every four years, is the cause.</p>
<p>Many of the people saying that may be seeking excuses. And yet scholars do think that subtle variations among soccer balls affect how they fly. Specifically, researchers increasingly believe that one variable really does differentiate soccer balls: their surfaces. It is harder to control a smoother ball, such as the much-discussed “Jabulani” used at the 2010 World Cup. The new ball used at this year’s tournament in Brazil, the “Brazuca,” has seams that are over 50 percent longer, one factor that makes the ball less smooth and apparently more predictable in flight.</p>
<p>“The details of the flow of air around the ball are complicated, and in particular they depend on how rough the ball is,” says John Bush, a professor of applied mathematics at MIT and the author of a recently published article about the aerodynamics of soccer balls. “If the ball is perfectly smooth, it bends the wrong way.”</p>
<p>By the “wrong way,” Bush means that two otherwise similar balls struck precisely the same way, by the same player, can actually curve in opposite directions, depending on the surface of those balls. Sound surprising?</p>
<p><strong>Magnus, meet Messi</strong></p>
<p>It may, because the question of how a spinning ball curves in flight would seem to have a textbook answer: the Magnus Effect. This phenomenon was first described by Isaac Newton, who noticed that in tennis, topspin causes a ball to dip, while backspin flattens out its trajectory. A curveball in baseball is another example from sports: A pitcher throws the ball with especially tight topspin, or sidespin rotation, and the ball curves in the direction of the spin.</p>
<p>In soccer, the same thing usually occurs with free kicks, corner kicks, crosses from the wings, and other kinds of passes or shots: The player kicking the ball applies spin during contact, creating rotation that makes the ball curve. For a right-footed player, the “natural” technique is to brush toward the outside of the ball, creating a shot or pass with a right-to-left hook; a left-footed player’s “natural” shot will curl left-to-right.</p>
<p>So far, so intuitive: Soccer fans can probably conjure the image of stars like Lionel Messi, Andrea Pirlo, or Marta, a superstar of women’s soccer, doing this. But this kind of shot — the Brazilians call it the “chute de curva” — depends on a ball with some surface roughness. Without that, this classic piece of the soccer player’s arsenal goes away, as Bush points out in his article, “The Aerodynamics of the Beautiful Game,” from the volume “Sports Physics,” published by Les Editions de L’Ecole Polytechnique in France.</p>
<p>“The fact is that the Magnus Effect can change sign,” Bush says. “People don’t generally appreciate that fact.” Given an absolutely smooth ball, the direction of the curve may reverse: The same kicking motion will not produce a shot or pass curving in a right-to-left direction, but in a left-to-right direction.</p>
<p><img src="https://newsoffice.mit.edu/sites/mit.edu.newsoffice/files/images/2014/MITnews_ScienceSoccerVideo.gif" /><br />
<span style="font-size:11px;"><em>In the above animation, a player strikes two balls: one smooth, and one with an elastic band wrapped around its equator. Both balls are struck with his instep so as to impart a counterclockwise spin. However, the smooth ball bends in the opposite direction as the banded ball. The presence of the elastic band changes the boundary layer on the ball surface from “laminar" to “turbulent." This is why all soccer balls have some surface roughness; otherwise, they would bend in the opposite direction as the ball's initial rotation. (Courtesy of the researchers.</em>)</span></p>
<p>Why is this? Bush says it is due to the way the surface of the ball creates motion at the “boundary layer” between the spinning ball and the air. The rougher the ball, the easier it is to create the textbook version of the Magnus Effect, with a “positive” sign: The ball curves in the expected direction.</p>
<p>“The boundary layer can be laminar, which is smoothly flowing, or turbulent, in which case you have eddies,” Bush says. “The boundary layer is changing from laminar to turbulent at different spots according to how quickly the ball is spinning. Where that transition arises is influenced by the surface roughness, the stitching of the ball. If you change the patterning of the panels, the transition points move, and the pressure distribution changes.” The Magnus Effect can then have a “negative” sign.</p>
<p><strong>From Brazil: The “dove without wings”</strong></p>
<p>If the reversing of the Magnus Effect has largely eluded detection, of course, that is because soccer balls are not absolutely smooth — but they have been moving in that direction over the decades. While other sports, such as baseball and cricket, have strict rules about the stitching on the ball, soccer does not, and advances in technology have largely given balls sleeker, smoother designs — until the introduction of the Brazuca, at least.</p>
<p>There is actually a bit more to the story, however, since sometimes players will strike balls so as to give them very little spin — the equivalent of a knuckleball in baseball. In this case, the ball flutters unpredictably from side to side. Brazilians have a name for this: the “pombo sem asa,” or “dove without wings.”</p>
<p>In this case, Bush says, “The peculiar motion of a fluttering free kick arises because the points of boundary-layer transition are different on opposite sides of the ball.” Because the ball has no initial spin, the motion of the surrounding air has more of an effect on the ball’s flight: “A ball that’s knuckling … is moving in response to the pressure distribution, which is constantly changing.” Indeed, a free kick Pirlo took in Italy’s match against England on Saturday, which fooled the goalkeeper but hit the crossbar, demonstrated this kind of action.</p>
<p>Bush’s own interest in the subject arises from being a lifelong soccer player and fan — the kind who, sitting in his office, will summon up clips of the best free-kick takers he’s seen. These include Juninho Pernambucano, a Brazilian midfielder who played at the 2006 World Cup, and Sinisa Mihajlovic, a Serbian defender of the 1990s.</p>
<p>And Bush happily plays a clip of Brazilian fullback Roberto Carlos’ famous free kick from a 1997 match against France, where the player used the outside of his left foot — but deployed the “positive” Magnus Effect — to score on an outrageously bending free kick. </p>
<p>“That was by far the best free kick ever taken,” Bush says. Putting on his professor’s hat for a moment, he adds: “I think it’s important to encourage people to try to understand everything. Even in the most commonplace things, there is subtle and interesting physics.”</p>
Sports, Mathematics, ResearchHigh-performance computing programming with ease
http://news.mit.edu/2014/high-performance-computing-programming-ease
Alan Edelman leads the global, open-source collaboration developing "Julia," a powerful but flexible programming language for high performance computing.Mon, 16 Jun 2014 17:10:02 -0400MIT Industrial Liaison Programhttp://news.mit.edu/2014/high-performance-computing-programming-ease<p>As high-performance computing (HPC) bends to the needs of "big data" applications, speed remains essential. But it's not only a question of how quickly one can compute problems, but how quickly one can program the complex applications that do so.</p>
<p>"In recent years, people have started to do many more sophisticated things with big data, like large-scale data analysis and large-scale optimization of portfolios," says Alan Edelman, a professor of applied mathematics who is affiliated with <a href="http://www.csail.mit.edu/" target="blank">MIT's Computer Science and Artificial Intelligence Laboratory</a>. "There's demand for everything from recognizing handwriting to automatically grading exams."</p>
<p>The challenge is that there are only so many programmers capable of such wizardry, and the programs are getting more and more complex and time-consuming to develop. "At HPC conferences, people tend to stand up and boast that they've written a program so it runs 10 or 20 times faster," Edelman says. "But it's the human time that in the end matters the most."</p>
<p>A few years ago, when an HPC startup Edelman was involved in — called Interactive Supercomputing — was acquired by Microsoft, he launched a new project with three others. The goal was to develop a new programming environment that was designed specifically for speed, but which would also reduce development time.</p>
<p>The group, which includes Jeff Bezanson, a PhD student at MIT, and Stefan Karpinski and Viral Shah, both formerly at the University of California at Santa Barbara, had all tried MPI (message-passing interface), which was specifically targeted at parallel processing. But MPI was tough going even for top-level programmers. "When you program in MPI, you're so happy to have finished the job and gotten any kind of performance at all, you'll never tweak it or change it," Edelman says.</p>
<p>The group set out to develop a programming language that could match MPI's parallel-processing support, while generating code that ran as fast as C. The key point, however, was that it would need to be as easy to learn and use as Matlab, Mathematica, Maple, Python, and R. To encourage rapid development of the language, as well as enhance collaboration, the language would need to be open-source, like Python and R.</p>
<p>In 2012, the project released the results of its labor, called "Julia," under an MIT open-source license. Although it's still a work in progress, <a href="http://julialang.org/" target="blank">Julia</a> has already met and far exceeded its requirements, Edelman says.</p>
<p>"Julia allows you to get in there and quickly develop something usable, and then modify the code in a very flexible way," Edelman says. "With Julia, we can play around with the code and improve it, and become very sophisticated very quickly. We're all superheroes now — we can do things we didn't even know we could do before."</p>
<p>On the surface, Julia is much like Matlab, and offers Lisp-like macros, making it easier for programmers to get started. It provides a zippy LLVM-based just-in-time compiler, distributed parallel execution, and high numerical accuracy. Julia also features a mathematical function library, most of which is written in Julia, as well as C and Fortran libraries.</p>
<p>But Julia differs significantly from Matlab and the other environments in ways that Edelman is only now beginning to understand. "It's one of those things where you just have to try it awhile," he says. "Once you get in there, you see it's like nothing you've ever seen before. With Julia, we're trying to change the way people solve a problem, almost by solving the problem without immediately trying to. It lets your program evolve to be the thing that you really imagined it to be, not just the first thing you wanted."</p>
<p>One innovation is Julia's concept of "multiple dispatch," which lets users define function behavior across combinations of argument types. This provides a dynamic type system broken down into types, enabling greater abstraction.</p>
<p>"Julia gives us the power of abstraction, which gives us performance, and allows us to deal with large data and create programs very quickly," says Edelman. "We sometimes have races between two equally good programmers, and the Julia programmer always wins."</p>
<p>Matlab and the other environments take previously written Fortran or C, or proprietary code, "and then glue it together with what I call bubble gum and paper clips," Edelman says. This offers the advantage of easy access to programs written in more difficult languages, but at a cost. "When you're ready to code yourself, you don't have the benefit of the Fortran or C speeds," he adds.</p>
<p>Julia, too, can integrate programs written in other languages. But "we also make it really easy to develop in Julia all the way down," Edelman explains. "With Julia, you don't face a big barrier when you need to get higher speeds. If you want to use other languages, it's fine, but if you want to do fancier things, the barrier to entry is much lower."</p>
<p>Edelman lives a "double life," he says. In addition to helping developing Julia, writing HPC applications, and teaching MIT students, he's also a theoretical mathematician with a focus on random matrix theory. In this role, Edelman is also a consumer of HPC simulations written in Julia: As he puts it, "I eat my own dog food."</p>
<p>Edelman spends a lot of time running Monte Carlo simulations, in which he generates a lot of random instances, and then tries to "understand collectively what might happen," he explains. "I love using Julia for Monte Carlo because it lends itself to lots of parallelism. I can grab as many processors as I need. I can grab shared or distributed memory from different computers and put them altogether. When you use one processor, it's like having a magnifying glass, but with Julia I feel like I've got an electron microscope. For a little while nobody else had that and it was all mine. I loved that."</p>
<p><strong>Open source helps kickstart global community</strong></p>
<p>The experience of co-developing Julia has deepened Edelman's belief in the power of open-source software. Thanks to Julia's open-source licensing, as well as the enthusiasm it generates among HPC developers, collaboration has been heightened in both the development of the language and in working together on Julia programs.</p>
<p>"We have hundreds of developers all over the world collaborating on Julia," Edelman says. "It's not like in the old days, when I would recruit the best Ph.D. students I could find at MIT and put them on a project. With Julia, people are joining us from around the world, and doing great things."</p>
<p>The open-source licensing has helped to quickly build an "incredible worldwide community," which Edelman says is just as important as the software's technical capabilities. "People are collaborating at so many levels it's amazing," he says. "Julia is out there, so I don't even know what's going to show up tomorrow morning. People will ask me if there's an optimization package of a certain kind for Julia, and I say, 'I guess not,' and then I wake up the next morning and somebody's just written one."</p>
<p>One key to accelerating the development of Julia was the decision to create a package manager that eases the development of add-ons. These include an IJulia app developed in conjunction with the IPython community that provides a browser-based graphical notebook interface.</p>
<p>As with most other programming languages, Julia lets you split a task up into different chunks. Julia is notable, however, for how easy it is to work on the same piece of software together, Edelman says. In one of his recent HPC classes at MIT, a student developed a project where one programmer could start developing Julia on one terminal, and let others start typing on the same code as well.</p>
<p>"All these students started typing together," Edelman says. "It was an experience I'd never seen before. It was a great party, and a lot of fun. It changes everything about developing software."</p>
Alan EdelmanFaculty, Research, Mathematics, Computer Science and Artificial Intelligence Laboratory (CSAIL), ProgrammingTomasz Mrowka named interim head of the Department of Mathematics
http://news.mit.edu/2014/tomasz-mrowka-named-interim-head-department-mathematics
Mon, 16 Jun 2014 16:31:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/tomasz-mrowka-named-interim-head-department-mathematics<p>Tomasz S. Mrowka, the Singer Professor of Mathematics, has been named interim head of the Department of Mathematics, effective immediately. Mrowka takes over the role from Michael Sipser, the Barton L. Weller Professor of Mathematics. On June 5, <a href="http://newsoffice.mit.edu/2014/michael-sipser-named-dean-school-science">Sipser was named dean</a> of the School of Science, after serving since last December as interim dean, and since 2004 as head of the Department of Mathematics.</p>
<p>Mrowka brings substantial experience as a researcher, educator, and administrator to his new role as interim department head. He received his SB in mathematics from MIT in 1983, and his PhD from the University of California at Berkeley in 1988, under the direction of Clifford Taubes and Robin Kirby. He taught at Stanford University, Caltech, and Harvard University before coming to MIT in 1996. He served as chair of the department's Graduate Student Committee from 1999 to 2002, and has chaired its Pure Mathematics Committee since 2004, with a one year pause in 2009-10.</p>
<p>Mrowka’s work mixes analysis, geometry, and topology, specializing in the use of partial differential equations, such as the Yang-Mills equations from particle physics, to analyze low-dimensional mathematical objects. Among his results is the joint discovery, with Robert Gompf of the University of Texas at Austin, of surprising four-dimensional models of space-time topology, going far beyond the expected examples envisaged by Kunihiko Kodaira and others.</p>
<p>In joint work with Peter Kronheimer of Harvard, Mrowka has settled longstanding conjectures posed by John Milnor, on the complexity of knots in three space, and by Rene Thom, on surfaces in four space. Mrowka and Kronheimer also revealed a deep structure underlying the Donaldson invariants of four-dimensional manifolds, which was an avatar of the Seiberg-Witten invariants. In further recent work with Kronheimer, Mrowka used these tools to show that a certain subtle combinatorially defined knot invariant introduced by Mikhail Khovanov can detect “knottedness.” </p>
<p>Mrowka’s joint work with Kronheimer has been honored by the American Mathematical Society with the 2007 Oswald Veblen Prize in Geometry and the 2010 Joseph L. Doob Prize for their monograph<em>, "</em>Monopoles and Three-Manifolds" (Cambridge University Press, 2007). Mrowka was elected a fellow of the American Academy of Arts and Sciences in 2007, and was named a Guggenheim fellow in 2010 and a fellow of the Radcliffe Institute for Advanced Studies in 2013.</p>
Tomasz MrowkaMathematics, FacultyLetter to MIT community announcing the new dean of science
http://news.mit.edu/2014/letter-mit-community-announcing-new-dean-science
Thu, 05 Jun 2014 14:00:00 -0400News Officehttp://news.mit.edu/2014/letter-mit-community-announcing-new-dean-science<p><em>The following email was sent today to the MIT community by Provost Martin Schmidt. </em></p>
<p>To the members of the MIT community,<br />
<br />
I am pleased to share the news that Michael Sipser, the Barton L. Weller Professor of Mathematics and former head of the Department of Mathematics, has agreed to serve as Dean of Science.<br />
<br />
Last December, former Dean Marc Kastner stepped down, having been nominated to lead the Office of Science in the US Department of Energy. Since then, Mike has served very ably in the role of interim dean and was warmly recommended by the committee I appointed (see box below) to search for a permanent dean.<br />
<br />
Trained as a mathematician and an engineer, Mike joined the MIT faculty shortly after earning his PhD from Berkeley. Since then, he has been a pioneer in theoretical computer science, written the standard textbook on the theory of computation and served as an enthusiastic and highly effective teacher. A member of CSAIL since 1979, Mike has lived out MIT’s commitment to working across disciplines and schools; the thesis students he supervises are as likely to come from Electrical Engineering and Computer Science as from Mathematics.<br />
<br />
Mike’s approach is measured, thoughtful and deliberate. For a decade, he led MIT’s Department of Mathematics, one of the top programs in the world, with impressive results. A calm and persuasive advocate, he was instrumental in working with donors to raise the funds to renovate Building 2. At the same time, he won the widespread respect and affection of faculty, students and staff for creating a warm, collegial community with a sense of humor. In facing the difficult human problems that arise in managing any group, Mike seeks the facts and works hard to arrive at balanced solutions. He will bring to the School of Science the same instinct to make sure that people feel valued, listened to and cared for.<br />
<br />
Mike has always loved teaching and explaining science; as interim dean, he has taken obvious pleasure in speaking on behalf of the many faculty candidates for promotions and tenure. His ability to make the case for fundamental research will be important both in Washington and in the upcoming Campaign. Mike is also personally committed to increasing diversity in STEM fields by actively building the pipeline of talent; thanks to Mike’s efforts, a program launched by one of his former PhD students, “Math Prize for Girls,” now brings hundreds of teen girls to our campus every fall to do competitive math for fun.<br />
<br />
I look forward to working with Mike in his new, permanent role. And I want to thank Search Committee chair Rebecca Saxe and her colleagues for the energy and time they poured into the process, and for identifying such a strong candidate to lead our School of Science.<br />
<br />
Sincerely,<br />
<br />
Marty Schmidt</p>
<hr />
<p><strong>Advisory Committee</strong></p>
<p>Paula Hammond, ChemE<br />
Tim Jamison, Chemistry<br />
John Joannopoulos, Physics<br />
Tom Mrowka, Mathematics<br />
Peter Reddien, Biology<br />
Rebecca Saxe, BCS, committee chair<br />
Sara Seager, EAPS</p>
MIT Administration, Mathematics, Faculty, School of ScienceMichael Sipser named dean of the School of Science
http://news.mit.edu/2014/michael-sipser-named-dean-school-science
Sipser has served as interim dean since Marc Kastner’s departure.Thu, 05 Jun 2014 13:30:08 -0400Anne Trafton | MIT News Officehttp://news.mit.edu/2014/michael-sipser-named-dean-school-science<p>Michael Sipser, the Barton L. Weller Professor of Mathematics and head of the Department of Mathematics since 2004, has been named dean of the School of Science.</p>
<p>Sipser has served as the school’s interim dean since December, when he was chosen to replace Marc Kastner, the Donner Professor of Physics; in November, President Barack Obama announced his intention to nominate Kastner to head the Department of Energy’s Office of Science.</p>
<p>“In 10 years as head of MIT’s Department of Mathematics, Mike Sipser sustained its extraordinary stature while building a warm sense of community,” MIT President L. Rafael Reif says. “His integrity, fairness, and patience will serve him very well in the role of dean. And as the School of Science faces difficult trends in federal funding, I believe Mike’s gift for explaining complex scientific concepts will be a tremendous asset in Washington.”</p>
<p>Sipser is a leading theoretical computer scientist and a member of MIT’s Computer Science and Artificial Intelligence Laboratory.</p>
<p>“Our community of faculty, students, and staff in the School of Science is extraordinary, and I’m honored to serve our people as dean,” Sipser says. “I look forward to working with the president and provost to maintain and expand our excellence in research and education, as well as to cultivate the spirits of wonder and play that have long been features of the MIT experience, so that MIT remains a place where brilliant and far-reaching discoveries are made.”</p>
<p>Under Sipser’s leadership, the Department of Mathematics has launched several successful fundraising efforts, securing funds for the renovation of Building 2, for endowed chairs, and for fellowships; thanks to these efforts, the department now provides fellowships to all first-year graduate students. During the same period, the department has seen a 64 percent increase in the number of undergraduate majors, from 236 in the 2003-04 academic year to 386 this year (including students who choose mathematics as a second major).</p>
<p>Sipser was also instrumental in bringing the Advantage Testing Foundation’s Math Prize for Girls, an annual math competition for high school girls, to MIT’s campus, where it has been held each fall since 2011.</p>
<p>During his tenure as interim dean, Sipser has already proven himself a thoughtful and deliberate leader, according to Provost Martin Schmidt.</p>
<p>“He’s an individual who doesn’t react impulsively but wants to understand the details, works hard to understand the facts, and then comes forward with thoughtful actions,” Schmidt says.</p>
<p>Sipser was chosen from a field of candidates identified by a faculty advisory committee chaired by Rebecca Saxe, an associate professor in the Department of Brain and Cognitive Sciences. The committee also included representatives of each of the other departments in the School of Science — math, chemistry, physics, biology, and Earth, atmospheric and planetary sciences.</p>
<p>Sipser says he looks forward to learning more about each of the school’s departments and continuing the community-building efforts he spearheaded in the math department. “The people in the School of Science are wonderful,” he says. “They are extraordinarily devoted to science and to MIT, and their research is amazing.”</p>
<p>Sipser is a fellow of the American Academy of Arts and Sciences. He authored the widely used textbook “Introduction to the Theory of Computation,” first published in 1996 and now in its third edition. Sipser received the MIT Graduate Student Council Teaching Award in 1984, 1989, and 1991, and the School of Science Student Advising Award in 2003.</p>
<p>A native of Brooklyn, N.Y., Sipser earned his BA in mathematics from Cornell University in 1974 and his PhD in engineering from the University of California at Berkeley in 1980. He joined MIT’s Laboratory for Computer Science as a research associate in 1979, becoming an assistant professor of applied mathematics in 1980; associate professor of applied mathematics in 1983; and professor of applied mathematics in 1989.</p>
<p>Sipser lives in Cambridge with his wife, Ina, and has two children: a daughter, Rachel, who recently graduated from New York University, and a son, Aaron, who is a high school junior.</p>
Michael SipserMIT Administration, Mathematics, Faculty, School of Science