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, 31 Aug 2015 13:48:01 -0400School 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 (Introduction to MATLAB Programming). 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 2012, after having taught 7.00 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 ScienceMinimal surfaces, maximal impact
http://news.mit.edu/2014/profile-mathematician-william-minicozzi-0604
MIT mathematician William Minicozzi unleashes ‘a wave of new results’ in geometric analysis.Wed, 04 Jun 2014 00:00:02 -0400Helen Knight | MIT News correspondenthttp://news.mit.edu/2014/profile-mathematician-william-minicozzi-0604<p>It’s something children do every day when blowing bubbles: Stick a circular wire in a pot of soapy water, pull it out, and behold the film forming across it.</p>
<p>But it’s not only children who are amused by this phenomenon — which has also kept mathematicians occupied since the 18th century, says William Minicozzi, a professor of mathematics at MIT.</p>
<p>That is because the film that forms across the wire pulls itself as tight as possible in order to minimize its surface tension. This results in a surface that has the least possible area for that fixed boundary. Even if you bend the wire, this so-called “minimal surface” will still form.</p>
<p>Mathematicians have studied minimal surfaces theoretically since the 1700s. Then in the 1880s, Belgian physicist Joseph Plateau began experimenting physically with these soapy films. He questioned whether for every possible curve that could be made to the wire, a minimal surface would form with that shape as its boundary. Although intuition would tell you that it should do this, there is no way to physically test the infinite number of possible variations that could be made to the shape of the wire in order to provide mathematical proof, Minicozzi says.</p>
<p><strong>A top geometric analyst</strong></p>
<p>Answering Plateau’s question — and addressing subsequent conjectures on the properties of complex minimal surfaces — has kept mathematicians busy ever since. The most notable of these researchers in recent years have been Minicozzi and his colleague Tobias Colding, the Cecil and Ida Green Distinguished Professor of Mathematics at MIT. Together, Minicozzi and Colding are widely considered to be the world’s leading geometric analysts of their generation.</p>
<p>In 2004 the duo jointly published a series of papers in the <em>Annals of Mathematics</em> that resolved a number of longstanding conjectures in the field; this earned them the prestigious Oswald Veblen Prize in Geometry.</p>
<p>Of particular interest to Minicozzi and Colding was whether it is possible to describe what all minimal surfaces look like. “Of course there are infinitely many possible minimal surfaces, because there are infinitely many possible ways of bending the curve, so you couldn’t list them all,” Minicozzi says. “But could you describe the way that they are all made? Could you give a recipe for building any minimal surface?”</p>
<p>The pair proved that all so-called “embedded minimal surfaces” — those that are not self-intersecting — can be cut into a collection of simple pieces where each is very flat (like a plane) or part of a helicoid. Helicoids are shaped like double-spiral staircases; the structures can also be found in many parking garages, Minicozzi says.</p>
<p>“If you drive into a parking garage and go up a level, that spiral ramp is part of a helicoid,” he says. “And one of the things we were able to show was that every embedded minimal surface could be built out of these things. So the minimal surface either looks like a nice flat thing where the area is bounded, or it looks exactly like one of these double spiral staircases.”</p>
<p><strong>‘A wave of new results’</strong></p>
<p>Awarding Minicozzi and Colding the Veblen Prize in 2010, the American Mathematical Society said the “profound” work had yielded a “remarkable global picture” for bounded minimal surfaces, and had “initiated a wave of new results.” </p>
<p>Minicozzi graduated from Princeton University in 1990, and moved to Stanford University to complete his PhD. He first began working with Colding in 1994, when the researchers were both at the Courant Institute at New York University. Together they solved a conjecture of Shing-Tung Yau that had been open since the 1970s concerning Riemannian manifolds, or curved spaces.</p>
<p>They continued collaborating after Minicozzi joined Johns Hopkins University in 1994, where he became a professor of mathematics in 2000 and a Krieger-Eisenhower Professor in 2007.</p>
<p>In 2012 Minicozzi joined MIT, where he was reunited with Colding; the researchers have recently been investigating how surfaces change over time, a process known as mean curvature flow. In particular, they have been looking at the formation of singularities, or conelike bumps where the smoothness of a surface breaks down.</p>
<p>They have been able to prove, he says, that of the infinite number of singularities that could possibly affect a surface through this curvature flow, only two types are stable enough to survive in reality. “If you were to wiggle your surface ever so slightly, in fact only two are stable of the infinitely many that are possible,” Minicozzi says. “So if you are trying to understand [mean curvature flow] and you have to deal with all of these cases, it’s much better to have to deal with two cases than an infinite number.”</p>
<p>This year Minicozzi and Colding have answered another open question in curvature flow: whether a given singularity — known as a “shrinker” — will appear different when viewed at different levels of magnification. “If you look at it under a more powerful microscope you may see an entirely different shrinker,” Minicozzi says.</p>
<p>Still fascinated by the field, the two researchers have already moved on to attempting to solve another longstanding conjecture in curvature flow.</p>
Mathematics, Faculty, Profile, GeometryGeorge Lusztig awarded the Shaw Prize in Mathematical Sciences
http://news.mit.edu/2014/george-lusztig-awarded-shaw-prize-mathematical-sciences
Mon, 02 Jun 2014 16:30:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/george-lusztig-awarded-shaw-prize-mathematical-sciences<p>George Lusztig, the Abdun-Nur Professor of Mathematics, was awarded <a href="http://www.shawprize.org/en">the Shaw Prize</a> in Mathematical Sciences for 2014. The Shaw Foundation cited Lusztig “for his fundamental contributions to algebra, algebraic geometry, and representation theory, and for weaving these subjects together to solve old problems and reveal beautiful new connections.”</p>
<p>The $1 million annual prize is awarded in three categories — astronomy, life science and medicine, and mathematical sciences — to individuals who have made outstanding contributions in academic and scientific research or applications. </p>
<p>After Lusztig graduated from the University of Bucharest in 1968, he received an master's and PhD from Princeton University in 1971 under the direction of Michael Atiyah and William Browder. He joined MIT's Department of Mathematics in 1978 following a professorship at the University of Warwick. </p>
<p>Through the 1970s and 1980s, Lusztig, in part with Pierre Deligne, gave a complete description of representations of finite Chevalley groups, the building blocks of finite symmetry groups. The Deligne–Lusztig description, introduced in 1976, uses the topology and geometry of Schubert varieties (a tool used to count solutions of algebraic equations). Correspondences identified in the Deligne-Lusztig description between the algebraic subtleties of representation theory and the geometric/topological subtleties of Schubert varieties would form a major theme in Lusztig’s work.</p>
<p>Lusztig would go on to show that many central problems in representation theory, such as those of real and <em>p</em>-adic groups, can be related to topology and geometry by means of Schubert varieties. This work would form the basis for many important recent developments, such as progress in the Langlands program and automorphic forms.</p>
<p>Beginning with a 1979 paper with David Kazhdan, and continuing through his most recent work, Lusztig has found combinatorial tools to describe the topology and geometry of Schubert varieties and the representations to which they are related. While these tools are easy to describe, they had not been used previously in mathematics.</p>
<p>“George Lusztig has unveiled profound connections between areas of mathematics that had previously been thought of as having no common overlap,” says Michael Sipser, interim dean of the School of Science. “In the course of doing so he shaped much of modern mathematics.”</p>
<p>In addition to the Shaw Prize, Lusztig has been distinguished with numerous honors. Among them are: the Berwick Prize of the London Mathematical Society; the AMS Cole Prize in Algebra; the Brouwer Medal of the Dutch Mathematical Society; and the AMS Leroy P. Steele Prize for Lifetime Achievement. Lusztig is a fellow of the Royal Society, a fellow of the American Academy of Arts and Sciences, and a member of the National Academy of Sciences.</p>
George LusztigAwards, honors and fellowships, Faculty, MathematicsEight School of Science faculty members granted tenure
http://news.mit.edu/2014/eight-school-science-faculty-members-granted-tenure-0530
Thu, 29 May 2014 16:00:01 -0400Bendta Schroeder | School of Sciencehttp://news.mit.edu/2014/eight-school-science-faculty-members-granted-tenure-0530<p>The School of Science recently announced that eight of its faculty members have been granted tenure by MIT.</p>
<p>“These people are extraordinary researchers and superb educators,” says Michael Sipser, interim dean of the School of Science. “Their work is brilliant, groundbreaking, and absolutely fascinating. I’m thrilled and honored to have them as new members of our tenured faculty.”</p>
<p>This year’s newly tenured associate professors are:</p>
<p><a href="http://bosaklab.scripts.mit.edu/">Tanja Bosak</a>, the Hayes Career Development Associate Professor in the Department of Earth, Atmospheric and Planetary Sciences, is an experimental geobiologist who studies the parallel evolution of microbial life and environmental systems in the Precambrian era. Bosak works to understand how biological, chemical, and physical processes combine to shape and preserve sedimentary rocks and influence geochemical trends at the Earth’s surface, using the shape and texture of microbial traces in the rock as a “smoking gun” for biological processes. </p>
<p><a href="http://boyerlab.mit.edu/people/principal-investigator/laurie-boyer">Laurie A. Boyer</a>, the Irvin and Helen Sizer Career Development Associate Professor in the Department of Biology, examines various transcriptional mechanisms that regulate mammalian cell differentiation, with particular emphasis on the role of DNA-packaging and non-coding regulatory elements in lineage commitment. Boyer focuses on the regulatory networks that control the development of heart cells, a process that requires the precise regulation of thousands of genes and that, when disrupted, results in congenital heart defects — the leading cause of infant morbidity and mortality and of adult cardiac dysfunction. </p>
<p><a href="http://jura.wi.mit.edu/cheeseman/">Iain M. Cheeseman</a>, an associate professor in the Department of Biology and member of the Whitehead Institute, analyzes the role of the kinetochore in chromosome segregation during mitosis and meiosis. The kinetochore, the protein interface that links chromosomes to microtubules, has been recognized as integral to cell division for more than a century, but analysis of its component proteins and mechanisms has been made possible only recently. Cheeseman has compiled a near-comprehensive list of human kinetochore proteins and is using it to examine kinetochore composition, structure, organization, and regulation, as well as the mechanism by which they achieve proper chromosome segregation. </p>
<p><a href="http://math.mit.edu/people/profile.php?pid=1225">Jacob Fox</a>, an assistant professor of applied mathematics, studies combinatorics, the branch of mathematics concerned with the properties of unstructured collections of discrete objects, such as graphs or sets. His specialties are probabilistic and extremal combinatorics, Ramsey theory, combinatorial geometry, and applications of combinatorics to theoretical computer science. He improved the relative Szemerédi theorem of Green and Tao and has given the first improvement in more than 50 years to estimates for hypergraph Ramsey numbers. He has also given solutions for several long-standing Erdős problems.</p>
<p><a href="http://math.mit.edu/~kelner/">Jonathan Kelner</a>, an assistant professor of applied mathematics and a member of the MIT Computer Science and Artificial Intelligence Laboratory, translates techniques from pure mathematics to fundamental problems in algorithms and complexity theory with an eye to real-world applications. He has worked in combinatorial optimization, spectral graph theory, distributed computing, machine learning, computational geometry and topology, computational biology, signal processing, and random matrix theory. His major advances include finding extremely fast algorithms for solving systems of linear equations and max flow problems.</p>
<p><a href="http://web.mit.edu/pog/www/">Paul O’Gorman</a>, an associate professor in the Department of Earth, Atmospheric and Planetary Sciences, works in the field of “moist dynamics” in climate science. He studies the influence of water vapor on the responses of the atmospheric general circulation and the hydrological cycle to climate change. O’Gorman has advanced our understanding of precipitation extremes, the intensity of and geographical extent of extra-tropical storm tracks, and the difference in warming between tropical oceans and land areas. He has developed a new effective static stability theory and created a new transformation to describe the upward shift of atmospheric variables in response to warming.</p>
<p><a href="http://mit.edu/perron/www/">J. Taylor Perron</a>, an assistant professor of geology in the Department of Earth, Atmospheric and Planetary Sciences, combines theory, observation, and lab experiments to reveal how a planet’s geologic and climatic histories are recorded in its topography. He creates computational models of landscape evolution and compares their predictions with field and remote sensing observations to discover new ways of reading a landscape’s history. He has made significant advances in identifying the origin of prominent landscape patterns, such as branching river networks, measuring the connection between precipitation, erosion and landforms to study conditions on planets and moons that are dramatically different from Earth — including the shorelines of ancient oceans on Mars and the methane rivers of Titan.</p>
<p><a href="http://www.saeijlab.com/InterLab/">Jeroen Saeij</a>, the Robert A. Swanson Career Development Professor of Life Sciences in the Department of Biology, studies host-parasite interactions and the genetics of susceptibility to infectious disease. Saeij focuses on the parasite <em>Toxoplasma gondii</em>, an obligate intracellular parasite that can infect any warm-blooded animal and cause severe disease in human infants or people with compromised immune systems. Saeij combines genetic, genomic, biochemical, and evolutionary approaches to identify host resistance genes and <em>Toxoplasma</em> virulence genes and to understand how their interactions determine the outcome of infection. </p>
Clockwise from top, left: Tanja Bosak, Laurie A. Boyer, Iain M. Cheeseman, Jacob Fox, Jeroen Saeij, J. Taylor Perron, Paul O'Gorman, and Jonathan Kelner Faculty, School of Science, Earth and atmospheric sciences, Biology, MathematicsLike father, like son
http://news.mit.edu/2014/profile-larry-guth-0527
Mathematician Larry Guth follows his physicist father, Alan, to a post on the MIT faculty.Tue, 27 May 2014 00:00:03 -0400Helen Knight | MIT News correspondenthttp://news.mit.edu/2014/profile-larry-guth-0527<p>Most people’s childhood memories of time spent with their fathers might involve practicing their swing in the park or going to see the big game. But for Larry Guth, a professor of mathematics at MIT, his fondest memories are of sitting with his father, talking about mathematics and physics.</p>
<p>Guth’s father is Alan Guth, the Victor F. Weisskopf Professor of Physics at MIT, and the originator of the theory of cosmic inflation, which describes the rapid expansion of the universe following the Big Bang, caused by a repulsive gravitational force.</p>
<p>As a teenager, Guth found his father’s theoretical physics difficult to understand, but he enjoyed discussing math problems with him. “We’d be talking about a particular question and I might describe an idea about it, and it would be a good idea but I would be very messy and write one thing on one part of the page and then one thing in another corner, and you really had to be with it to understand what I was talking about,” Guth says. “So he would very systematically write it down line by line, and then you could see what I was talking about.”</p>
<p>Now teaching at MIT, Guth tries to encourage his students to follow the same simple, systematic approach to their work. “We both really enjoy teaching, and the way [my father] approached problems back then is how I like to go about explaining things to my students now,” he says.</p>
<p><strong>Shaping up</strong></p>
<p>Guth moved to MIT as a graduate student, where he began studying geometry under the supervision of mathematics professor Tomasz Mrwoka. In particular, he became interested in different ways to describe the size of shapes. “If you have a rectangle, for example, everyone knows that you should describe its length and its width,” he says. “But then suppose you just have some unknown region, and you would like to describe to someone its shape in just a few numbers. Is there something like the length, or the width, that makes an arbitrary shape?”</p>
<p>It turns out that there is. The length of any arbitrary shape is the longest distance between two points in the region, while the width describes how far you would have to travel — starting from any point in the region — to get out of it, Guth says. “So in this way you can generalize these familiar notions of length and width as a way of describing arbitrary shapes, and then you can start to ask questions like, ‘Is there a shape with a particular set of parameters? Is there a shape whose width is larger than its length — although that sounds weird and counterintuitive?’”</p>
<p>After completing his PhD, Guth moved as a postdoc to Stanford University, where he originated some questions in geometry concerning “area-contracting putty,” or the manipulation of jellylike blobs with unusual physical properties into different shapes and dimensions.</p>
<p>More recently, his research focus has been on combinatorics, or the study of discrete structures, and how sets of lines intersect each other in space. In particular he has devoted a great deal of effort to the so-called “Kakeya problem,” considering how cylinders in space can overlap each other, where he has been able to use tricks from his background in geometry to help simplify the problem.</p>
<p>He also studies harmonic analysis, investigating how sound waves interact with each other. So for example, when a bell rings and the sound waves spread out, they form a sphere of high pressure around the instrument — which is, in turn, surrounded by a larger, concentric sphere of low pressure. These regions of high and low pressure continue to alternate as they spread out from the bell. “Now imagine there is a really complex device producing the sound, which you could model as 1 million bells, each producing these waves with high- and low-pressure regions,” Guth says.</p>
<p>Where regions of high and low pressure meet, the two typically cancel each other out, he says. “So the kind of problem I’m interested in is estimating how often that happens: Are there some configurations [of sound waves] where there is not so much cancellation?”</p>
<p><strong>The play’s the thing</strong></p>
<p>Outside of his research, Guth has always enjoyed acting, and he regularly invites friends over to read plays aloud together. Not only does it provide a release from the frustrations of studying complex problems, but it also has pleasing similarities with mathematics, he says.</p>
<p>“Math has this perception of being forbiddingly complicated, which there is some truth to,” Guth says. “But on the other hand we are interested in simple things that people could take for granted, like numbers, circles, and lines, and so there is an element to math of not taking these things for granted and being more interested in them than the average bear.”</p>
<p>Similarly, in acting, you cannot take your character’s actions for granted, he says. “You have to think about what your character is going through and take it more seriously than you might at first sight.”</p>
<p>Guth still enjoys spending time with his father, discussing math and physics, and now that they are both at MIT the pair regularly meet up for lunch around campus. These days, though, it is difficult for either of them to understand the work the other does, Guth says. “We still try, but rather than explaining our own research it’s often more fun to talk about more classical problems in physics and math, which are cooler, and a little bit more accessible for both of us.”</p>
Larry Guth, a professor of mathematics at MITFaculty, Profile, MathematicsSperm cells are extremely efficient at swimming against a current
http://news.mit.edu/2014/sperm-cells-are-extremely-efficient-swimming-against-current-0527
Study may explain how sperm travel long distances, through difficult terrain, to reach an egg.Tue, 27 May 2014 00:00:01 -0400Helen Knight | MIT News correspondenthttp://news.mit.edu/2014/sperm-cells-are-extremely-efficient-swimming-against-current-0527<p>Like salmon traveling upstream to spawn, sperm cells are extremely efficient at swimming against the current, according to research to be published this week.</p>
<p>The discovery, to be published in the journal <em>eLife </em>by researchers at MIT and Cambridge University, may help us to understand how some sperm travel such long distances, through difficult terrain, to reach and fertilize an egg.</p>
<p>Of the hundreds of millions of sperm cells that begin the journey up the oviducts, only a few hardy travelers will ever reach their destination. Not only do the cells have to swim in the right direction over distances that are around 1,000 times their own length, but they are exposed to different chemicals and currents along the way.</p>
<p>While we know that sperm cells can “smell” chemicals given off by the egg once they get very close to it, this does not explain how they navigate for the majority of their journey, says Jörn Dunkel, an assistant professor of mathematics at MIT, and a member of the research team.</p>
<p>“We wanted to know which physical mechanisms could be responsible for navigation,” says Dunkel, who carried out the research alongside Vasily Kantsler of the Skolkovo Institute of Science and Technology and the University of Warwick (and currently visiting at MIT); Raymond E. Goldstein of Cambridge; and Martyn Blayney of the Bourn Hall Clinic in the U.K. “If you think of salmon, for example, they can swim against the stream, and the question was whether something similar could really be confirmed for human sperm cells.”</p>
<p><strong>Microchannels in lieu of oviducts</strong></p>
<p>However, observing sperm cells swimming within the human body itself is no easy task. So in a bid to understand what the cells are capable of, the researchers instead built a series of artificial microchannels of different sizes and shapes, into which they inserted the sperm. They were then able to modify the flow of fluid through the tubes, to investigate how the cells responded to different current speeds.</p>
<p>They discovered that at certain flow speeds, the sperm cells were able to swim very efficiently upstream. “We found that if you create the right flow velocities, you can observe them swimming upstream for several minutes,” Dunkel says. “The mechanism is very robust.”</p>
<p>What’s more, the researchers were also surprised to observe that the sperm were not swimming in a straight line upstream, but in a spiraling motion, along the walls of the channel. The sperm cells react to the difference in the speed of current near the walls of the chamber — where the fluid is attracted to the surface, and is therefore at its slowest — and the free-flowing center of the tube, Dunkel says.</p>
<p>If biologists are able to observe similar fluid-flow speeds within the oviduct, it could help confirm whether sperm cells are indeed using this mechanism to navigate through the body, he says.</p>
<p><strong>Possible advances in artificial insemination</strong></p>
<p>Not only would this improve our understanding of human reproduction, but it could also one day allow us to design new diagnostic tools and more efficient artificial-insemination techniques, the researchers claim. Reproduction specialists could take sperm samples and artificially recreate the conditions within the body to identify the cells that are the best swimmers, in a bid to preselect those most likely to succeed, Dunkel says.</p>
<p>The researchers can also experiment with different fluid viscosities within the microchannels, to determine which result in the strongest upstream swimming effect, he says. “So the idea would be to fine-tune the properties of the fluid medium that the sperm cells are contained in, before you insert it into the body, so that you know the cells can achieve optimal upstream swimming.”</p>
<p>Jackson Kirkman-Brown, honorary reader in reproductive science at the University of Birmingham and science lead for the Birmingham Women’s Fertility Centre, both in the U.K., says the research gives us an important new insight into a mechanism that sperm may be using to navigate inside the human body.</p>
<p>“We really know effectively nothing about how sperm cells navigate, so this gives us more information about a potential mechanism that may be important,” he says. “It’s telling us that human sperm seem to move differently to other things that propel themselves with a tail.”</p>
<p>However, much more work will be needed to determine if sperm cells behave in the same way in the much more complex terrain inside the oviduct itself. “This is a huge step in understanding what might influence sperm in that environment, but it’s far from explaining what does influence them,” Kirkman-Brown says. “People will certainly try to find this mechanism happening [inside the body], but it’s going to be a complicated chase.”</p>
<p>In the meantime, the researchers plan to begin investigating whether sperm cells can work together to reach the egg. “It is a commonly held belief that there is competition between sperm cells, with the fittest reaching the egg first,” Dunkel says. “But recent studies by our team and others show that sperm practically always accumulate at the surface of a tube, and you can end up with a high local concentration of sperm cells, so there could actually be cooperation among these cells that allows them to swim faster collectively.”</p>
<p>The research was supported by the European Research Council.</p>
Superimposed photographs of a human sperm cell swimming upstream along the wall of a microfluidic channel, with overlaid virtual tracer particles indicating the flow direction. Reproduction, Microfluidics, Fluid dynamics, Mathematics, School of ScienceComputer system automatically solves word problems
http://news.mit.edu/2014/computer-system-automatically-solves-word-problems-0502
Applications could include educational tools, systems to solve practical geometry or physics problems.Fri, 02 May 2014 00:00:04 -0400Larry Hardesty | MIT News Officehttp://news.mit.edu/2014/computer-system-automatically-solves-word-problems-0502<p>Researchers in MIT’s Computer Science and Artificial Intelligence Laboratory, working with colleagues at the University of Washington, have developed a new computer system that can automatically solve the type of word problems common in introductory algebra classes.</p>
<p>In the near term, the work could lead to educational tools that identify errors in students’ reasoning or evaluate the difficulty of word problems. But it may also point toward systems that can solve more complicated problems in geometry, physics, and finance — problems whose solutions don’t appear in the back of the teacher’s edition of a textbook.</p>
<p>According to Nate Kushman, an MIT graduate student in electrical engineering and computer science and lead author on the new paper, the new work is in the field of “semantic parsing,” or translating natural language into a formal language such as arithmetic or formal logic. Most previous work on semantic parsing — including <a href="http://newsoffice.mit.edu/2013/writing-programs-using-ordinary-language-0711">his own</a> — has focused on individual sentences, Kushman says. “In these algebra problems, you have to build these things up from many different sentences,” he says. “The fact that you’re looking across multiple sentences to generate this semantic representation is really something new.”</p>
<p>Kushman is joined on the paper by Regina Barzilay, a professor of computer science and engineering and one of his two thesis advisors, and by the University of Washington’s Yoav Artzi and Luke Zettlemoyer. The researchers will present their work at the annual meeting of the Association for Computational Linguistics in June.</p>
<p><strong>Finding your place</strong></p>
<p>The researchers’ system exploits two existing computational tools. One is the computer algebra system <a href="http://en.wikipedia.org/wiki/Macsyma">Macsyma</a>, whose initial <a href="http://esd.mit.edu/Faculty_Pages/moses/Macsyma.pdf">development at MIT</a> in the 1960s was a <a href="http://www.scottaaronson.com/blog/?p=524">milestone</a> in artificial-intelligence research. For Kushman and his colleagues’ purposes, Macsyma provided a way to distill algebraic equations with the same general structure into a common template.</p>
<p>The other tool is the type of sentence parser used in most natural-language-processing research. A parser represents the parts of speech in a given sentence and their syntactic relationships as a tree — a type of <a href="http://newsoffice.mit.edu/2012/explained-graphs-computer-science-1217">graph</a> that, like a family-tree diagram, fans out at successive layers of depth.</p>
<p>For the researchers’ system, understanding a word problem is a matter of correctly mapping elements in the parsing diagram of its constituent sentences onto one of Macsyma’s equation templates. To teach the system how to perform that mapping, and to produce the equation templates, the researchers used machine learning.</p>
<p>Kushman found a website on which algebra students posted word problems they were having difficulty with, and where their peers could then offer solutions. From an initial group of roughly 2,000 problems, he culled 500 that represented the full range of problem types found in the larger set.</p>
<p>In a series of experiments, the researchers would randomly select 400 of the 500 problems, use those to train their system, and then test it on the remaining 100.</p>
<p>For the training, however, they used two different approaches — or, in the parlance of machine learning, two different types of supervision. In the first approach, they fed the system both word problems and their translations into algebraic equations — 400 examples of each. But in the second, they fed the system only a few examples of the five most common types of word problems and their algebraic translations. The rest of the examples included only the word problems and their numerical solutions.</p>
<p>In the first case, the system, after training, was able to solve roughly 70 percent of its test problems; in the second, that figure dropped to 46 percent. But according to Kushman, that’s still good enough to offer hope that the researchers’ approach could generalize to more complex problems.</p>
<p><strong>Featured performance</strong></p>
<p>In determining how to map natural language onto equation templates, the system examined hundreds of thousands of “features” of the training examples. Some of those features related specific words to problem types: For instance, the appearance of the phrase “react with” was a good indication that the problem dealt with chemistry. Other features looked at the location of specific words in parsing diagrams: The appearance of the word “costs” as the main verb indicated a great deal about which sentence elements should be slotted into which equation templates.</p>
<p>Other features simply analyzed the syntactical relationships between words, regardless of the words themselves, while still others examined correlations between words’ locations in different sentences. Finally, Kushman says, he included a few “sanity check” features, such as whether or not the solution yielded by a particular equation template was a positive integer, as is almost always the case with algebraic word problems.</p>
<p>“The idea of this kind of supervision they have will be useful for lots of things,” says Kevin Knight, a professor of computer science of the University of Southern California. “The approach of building a generative story of how people get from text to answers is a great idea.”</p>
<p>The system’s ability to perform fairly well even when trained chiefly on raw numerical answers is “super-encouraging,” Knight adds. “It needs a little help, but it can benefit from a bunch of extra data that you haven’t labeled in detail.”</p>
This image shows a word problem provided by the researchers. The answer appears in the second image.Machine learning, Mathematics, Electrical Engineering & Computer Science (eecs)Seven faculty members elected to the American Academy of Arts and Sciences
http://news.mit.edu/2014/seven-faculty-members-elected-american-academy-arts-and-sciences
Among 204 elected this year to the prestigious honorary society.Wed, 23 Apr 2014 17:00:00 -0400News Officehttp://news.mit.edu/2014/seven-faculty-members-elected-american-academy-arts-and-sciences<p>Seven MIT faculty members are among 204 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=217">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>Elazer Reuven Edelman, the Thomas D. and Virginia W. Cabot Professor of Health Sciences and Technology</li>
<li>Michael Greenstone, the 3M Professor of Environmental Economics</li>
<li>Keith Adam Nelson, a professor of chemistry</li>
<li>Paul A. Seidel, a professor of mathematics</li>
<li>Gigliola Staffilani, the Abby Rockefeller Mauzé Professor of Mathematics</li>
<li>Sherry Roxanne Turkle, the Abby Rockefeller Mauzé Professor of the Social Studies of Science and Technology</li>
<li>Robert Dirk van der Hilst, the Schlumberger Professor of Earth Sciences and head of the Department of Earth, Atmospheric and Planetary Sciences</li>
</ul>
<p>“It is a privilege to honor these men and women for their extraordinary individual accomplishments,” Don Randel, chair of the academy’s Board of Directors, said in a statement. “The knowledge and expertise of our members give the Academy a unique capacity — and responsibility — to provide practical policy solutions to the pressing challenges of the day. We look forward to engaging our new members in this work.”</p>
<p>The new class will be inducted at a ceremony held on Oct. 11 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>
Faculty, Awards, honors and fellowships, AAAS, Health sciences and technology, Economics, Chemistry, Mathematics, science, Technology, Technology and society, Earth sciencesMIT students dominate Putnam Mathematical Competition, winning team event
http://news.mit.edu/2014/mit-students-dominate-putnam-mathematical-competition-winning-team-event
Four of five top individual finishers, known as “Putnam Fellows,” also hail from MIT.Tue, 08 Apr 2014 16:35:31 -0400Chuck Leddy, MIT News correspondenthttp://news.mit.edu/2014/mit-students-dominate-putnam-mathematical-competition-winning-team-event<p>The recently announced results of the annual <a href="http://math.scu.edu/putnam/index.html">William Lowell Putnam Mathematical Competition</a>, the prestigious undergraduate mathematics contest that this year included more than 4,100 students from 557 colleges and universities across the U.S. and Canada, represented a sweeping victory for MIT.</p>
<p>The Institute not only won the team competition — placing ahead of runners-up Carnegie Mellon University and Stanford University — but also placed four students in the top five individual spots, an achievement that earns those contestants designation as “Putnam Fellows”: sophomore Mitchell Lee, junior Zipei Nie, freshman Bobby Shen, and freshman David Yang.</p>
<p>A large number of other MIT students also delivered <a href="http://math.mit.edu/news/spotlight/documents/2014_04_02_Putnam.pdf">strong performances</a> on the famously challenging six-hour, 12-question exam.</p>
<p>“The Putnam exam is brutally graded,” explains Henry Cohn, an adjunct professor of applied mathematics who helped students prepare for the Putnam by teaching — along with Abhinav Kumar, an associate professor of applied mathematics — 18.A34 (Problem Solving Seminar). “There’s almost no partial credit given, so, for example, on question B6 this year, <a href="http://tech.mit.edu/V134/N16/graphics/putnam.html">exactly zero students received full credit</a>. This year’s median score was around one point out of 120 points available, so even students who scored zero were in good company.”</p>
<p>“There were 87 MIT students in the top 442 this year, which is amazing,” Cohn adds. “No other school had even half that many.”</p>
<p>Cohn and members of MIT’s team first learned of the Putnam triumph via Wikipedia.</p>
<p>“We noticed a day or two before we received the ‘official’ results in the mail that somebody had altered the Wikipedia entry for the Putnam Competition to reflect that MIT had won, but we didn’t know if it was a prank,” he says. “When the ‘official’ results finally came, I was thrilled.”</p>
<p><strong>Winning MIT team of Lee, Nie, and Gunby</strong></p>
<p>The three members of MIT’s winning team — Lee, Nie, and junior Benjamin Gunby, also a mathematics major — competed in Putnam for a variety of reasons.</p>
<p>“I find the Putnam Competition to be a fun experience,” explains Lee, a mathematics major and two-time Putnam Fellow. “Besides that, I hope that my performance will help me if I apply for graduate school. I also appreciate the prize money.” (Lee won $3,500 for his efforts.)</p>
<p>Lee also enjoys the team camaraderie. He attributes MIT’s performance this year to “the overall strength of the math community here at MIT.”</p>
<p>“We enjoy talking about math,” he says. “We all support each other and congratulate each other. The things I have learned from other competitors undoubtedly played a role in my own performance.”</p>
<p>Nie, also a mathematics major and two-time Putnam Fellow, says that math contests provide a sense of belonging. As a high school student in China, Nie says, he felt “pessimistic day after day, so I decided to let math be the meaning of my life. Math and the support of my high school teachers cured me. Math Olympiad training became my main work during those years. Fortunately, I made great progress.”</p>
<p>Gunby, a Putnam Fellow last year and a member of the winning MIT trio this year, says math contests represent an intellectual challenge. “Math competitions have played a big part of my life,” he says, “especially during high school. Before college, math classes didn’t do much to improve my problem-solving skills. But everyone in college can find a math class that’s interesting and challenging.”</p>
<p>Michael Sipser, the Barton L. Weller Professor of Mathematics, head of the Department of Mathematics, and interim dean of the School of Science, says: “I’m proud that our department has attracted such a high caliber of student. We had an extraordinary number of top performers on the Putnam: 80 percent of the top five and 60 percent of the top 25.”</p>
<p>“Word has gotten out that MIT is the place to be for competitive math,” Sipser says, “and success breeds even more success. Winning helps us attract even more strong students, and not just math competitors, but smart kids in general.”</p>
<p>Sipser hopes that attention on events like the Putnam Competition can trigger larger public conversations about math. “It helps us celebrate math in a playful way,” he says.</p>
<p><strong>Contest math vs. research math</strong></p>
<p>How well does success at “contest math,” like the Putnam Competition, correlate with later achievement in math? As Sipser puts it, comparing time-limited contest math to research math “is like comparing regular chess to blitz chess.”</p>
<p>Bjorn Poonen, the Claude E. Shannon Professor of Mathematics and one of just eight students ever to be a four-time Putnam Fellow (as an undergraduate at Harvard University), agrees: “The Putnam differs from math research in that it rewards speed more than the ability to develop deep insights over time. There is some overlap in the skills, but there are many excellent mathematicians who didn’t do well on the Putnam. Also, as far as content goes, math majors at MIT learn much more than what is covered on the Putnam.”</p>
<p>Cohn, who received his SB in mathematics from MIT in 1995 and who participated in the Putnam Competition as an undergraduate, says: “While we rightfully celebrate these clever and quick problem-solvers who did so well on the Putnam, there are amazing MIT students who don’t even take the exam, as well as wonderful students who are going to accomplish fantastic things in mathematics even though they scored one point on the Putnam. The mathematics department doesn’t value students who win contests any more than we value the rest of our great students.”</p>
Mathematics, Awards, honors and fellowships, Students, UndergraduateIn the cloud: How coughs and sneezes float farther than you think
http://news.mit.edu/2014/coughs-and-sneezes-float-farther-you-think
Novel study uncovers the way coughs and sneezes stay airborne for long distances.Tue, 08 Apr 2014 00:00:02 -0400Peter Dizikes | MIT News Officehttp://news.mit.edu/2014/coughs-and-sneezes-float-farther-you-think<p>The next time you feel a sneeze coming on, raise your elbow to cover up that multiphase turbulent buoyant cloud you’re about to expel.</p>
<p>That’s right: A novel study by MIT researchers shows that coughs and sneezes have associated gas clouds that keep their potentially infectious droplets aloft over much greater distances than previously realized.</p>
<p>“When you cough or sneeze, you see the droplets, or feel them if someone sneezes on you,” says John Bush, a professor of applied mathematics at MIT, and co-author of a new paper on the subject. “But you don’t see the cloud, the invisible gas phase. The influence of this gas cloud is to extend the range of the individual droplets, particularly the small ones.”</p>
<p>Indeed, the study finds, the smaller droplets that emerge in a cough or sneeze may travel five to 200 times further than they would if those droplets simply moved as groups of unconnected particles — which is what previous estimates had assumed. The tendency of these droplets to stay airborne, resuspended by gas clouds, means that ventilation systems may be more prone to transmitting potentially infectious particles than had been suspected.</p>
<p>With this in mind, architects and engineers may want to re-examine the design of workplaces and hospitals, or air circulation on airplanes, to reduce the chances of airborne pathogens being transmitted among people.</p>
<p>“You can have ventilation contamination in a much more direct way than we would have expected originally,” says Lydia Bourouiba, an assistant professor in MIT’s Department of Civil and Environmental Engineering, and another co-author of the study.</p>
<p>The paper, “Violent expiratory events: on coughing and sneezing,” was published in the <em>Journal of Fluid Mechanics</em>. It is co-written by Bourouiba, Bush, and Eline Dehandschoewercker, a graduate student at ESPCI ParisTech, a French technical university, who previously was a visiting summer student at MIT, supported by the MIT-France program.</p>
<p><strong>Smaller drops, longer distances</strong></p>
<p>The researchers used high-speed imaging of coughs and sneezes, as well as laboratory simulations and mathematical modeling, to produce a new analysis of coughs and sneezes from a fluid-mechanics perspective. Their conclusions upend some prior thinking on the subject. For instance: Researchers had previously assumed that larger mucus droplets fly farther than smaller ones, because they have more momentum, classically defined as mass times velocity.</p>
<p>That would be true if the trajectory of each droplet were unconnected to those around it. But close observations show this is not the case; the interactions of the droplets with the gas cloud make all the difference in their trajectories. Indeed, the cough or sneeze resembles, say, a puff emerging from a smokestack.</p>
<p>“If you ignored the presence of the gas cloud, your first guess would be that larger drops go farther than the smaller ones, and travel at most a couple of meters,” Bush says. “But by elucidating the dynamics of the gas cloud, we have shown that there’s a circulation within the cloud — the smaller drops can be swept around and resuspended by the eddies within a cloud, and so settle more slowly. Basically, small drops can be carried a great distance by this gas cloud while the larger drops fall out. So you have a reversal in the dependence of range on size.”</p>
<p>Specifically, the study finds that droplets 100 micrometers — or millionths of a meter — in diameter travel five times farther than previously estimated, while droplets 10 micrometers in diameter travel 200 times farther. Droplets less than 50 micrometers in size can frequently remain airborne long enough to reach ceiling ventilation units.</p>
<p>A cough or sneeze is a “multiphase turbulent buoyant cloud,” as the researchers term it in the paper, because the cloud mixes with surrounding air before its payload of liquid droplets falls out, evaporates into solid residues, or both.</p>
<p>“The cloud entrains ambient air into it and continues to grow and mix,” Bourouiba says. “But as the cloud grows, it slows down, and so is less able to suspend the droplets within it. You thus cannot model this as isolated droplets moving ballistically.”</p>
<div class="cms-placeholder-content-video"></div>
<p><strong>Ready for a close-up</strong></p>
<p>Other scholars say the findings are promising. Lidia Morawska, a professor at Queensland University of Technology in Brisbane, Australia, who has read the study, calls it “potentially a very important paper” that suggests people “might have to rethink how we define the airborne respiratory aerosol size range.” However, Morawska also notes that she would still like to see follow-up studies on the topic.</p>
<p>The MIT researchers are now developing additional tools and studies to extend our knowledge of the subject. For instance, given air conditions in any setting, researchers can better estimate the reach of a given expelled pathogen. </p>
<p>“An important feature to characterize is the pathogen footprint,” Bush says. “Where does the pathogen actually go? The answer has changed dramatically as a result of our revised physical picture.”</p>
<p>Bourouiba’s continuing research focuses on the fluid dynamics of fragmentation, or fluid breakup, which governs the formation of the pathogen-bearing droplets responsible for indoor transmission of respiratory and other infectious diseases. Her aim is to better understand the mechanisms underlying the epidemic patterns that occur in populations. </p>
<p>“We’re trying to rationalize the droplet size distribution resulting from the fluid breakup in the respiratory tract and exit of the mouth,” she says. “That requires zooming in close to see precisely how these droplets are formed and ejected.”</p>
<p>Funding for the study was provided by the National Science Foundation.</p>
Mathematics, Medicine, Public health, Civil and environmental engineering, Health, Fluid dynamicsHow to beat others to the mathematical punch
http://news.mit.edu/2014/how-to-beat-others-to-the-mathematical-punch
New MITx MOOC brings the street fighting approach to solving math problems.Fri, 28 Mar 2014 11:00:01 -0400Sara Sezun and Steve Carson | Office of Digital Learninghttp://news.mit.edu/2014/how-to-beat-others-to-the-mathematical-punch<p>In a street fight, there are no rules of engagement. To win, you need to think quickly and do the unconventional. Sanjoy Mahajan, visiting associate professor in the Department of Electrical Engineering, brings this no-holds-barred spirit to his upcoming <i>MITx</i> course, <a href="https://www.edx.org/course/mitx/mitx-6-sfmx-street-fighting-math-1501#.UzR3615w1BI" target="_blank">6.SFMx Street-Fighting Math</a>, which starts April 8 and is open for registration on the edX platform. Mahajan will teach students how to calculate approximations in real-life situations, to arrive at an educated guess when exact answers are not easy to obtain.</p>
<p>Mahajan begins the first class of his residential course by writing on the board, “Rigor leads to rigor mortis.” He believes math should be fun, and criticizes methods that rely on rote memorization to teach math. He says, “Because of rigor mortis, people think I do it right, or I don’t do it," an attitude that intimidates many students. Mahajan likens math to physics experiments. “You investigate it, just like you investigate the world, as a giant laboratory with objects, devices, and patterns.”</p>
<p>One of Mahajan’s major research interests is improving the teaching of math and science by doing away with rote memorization, which he calls “brittle knowledge that doesn’t transfer to any new problem. For instance, in quadratic equations, students have a hard time using ‘y’ as a variable, because they’re always so used to using ‘x’.” He explains that while learning algebra, “[Students] didn’t understand what they were doing. They saw the pattern of using ‘x’ as a pin mark, but didn’t understand its meaning. They only remembered the order of symbols in a formula; they didn’t understand the meaning of what they were doing.”</p>
<p>Applying rigid formulas without considering their consequences can lead to serious mistakes. For example, when asked the answer to "6 x 3", most children give it correctly as 18, because they have memorized multiplication tables. When asked to write a story problem for this equation, the most common example deals with ducks in a pond. Children will typically write a problem that describes six ducks in a pond, joined by three more ducks. When the children ask how many ducks there are in total, they expect the answer to be 18, because they are following a pattern set by the equation. They do not stop to examine the facts, and consider the difference between addition and multiplication. Unfortunately, many children continue this habit of applying formulas without critical thinking throughout their school years.</p>
<p>To disseminate his innovative approach, Mahajan began teaching Street-Fighting Math in 2007 during the Independent Activities Period, a time in January before regular classes begin when MIT students can take enrichment courses. The residential course will be taught this semester during the last seven weeks. The curriculum will be exactly the same in terms of rigor and materials for both residential and <i>MITx</i> students. The only difference is that the residential students will be learning the curriculum a week before the <i>MITx</i> students, to test the materials before they go online.</p>
<p>Street-fighting math will have no lectures, just short videos of Mahajan explaining problem sets, which students will have to work on. The problems will be graded immediately by the computer. Mahajan explains, “The advantage is that students see the answer right away, while they’re still thinking about the problem . . . Lots of research shows that for feedback to be effective, it’s best for it to be immediate.” If the answer is wrong, “Students will have links to help them understand each problem, which will lead them to pieces in the reading (assignments), that will help them understand the problem.”</p>
<p>Along with teaching 6.SFMx, Mahajan will be conducting research on how students learn online, but he is still working on the details. “I’m learning too,” he says. “It’s my first online course.”</p>
<p>Mahajan is looking forward to the edX course, to reaching “people who have a math background, but it’s been wasted.” He wants to “teach if for the whole world”, to generate more enthusiasm for learning math, because it “can help you understand things. It can show you how the pieces of the world are put together.”</p>
<p>To give an actual example of street-fighting math in action, Mahajan tells a story from his teaching days at Cambridge, many years ago. Borders had just opened a new store in Cambridge and was holding a contest. They had a gigantic jar filled with beans, and were offering a prize for guessing the correct number. A group of Mahajan’s students entered the contest and won. They applied Mahajan’s method of breaking down difficult problems into easier ones, by counting the beans in each dimension: height, width, and depth. Then they multiplied these numbers to arrive at an approximate answer. “I call it divide-and-conquer reasoning,” says Mahajan. “It worked for the British to rule India, and it works for problem-solving.”</p>
EdX, Faculty, MITx, Massive open online courses (MOOCs), MathematicsU.S. News ranks MIT’s graduate program in Engineering No. 1; Sloan is No. 5 business school
http://news.mit.edu/2014/us-news-ranks-mits-graduate-program-in-engineering-no-1-sloan-is-no-5-business-school-0311
Institute’s programs rank first in 7 engineering, 5 science, and 3 business fields.Tue, 11 Mar 2014 00:01:00 -0400News Officehttp://news.mit.edu/2014/us-news-ranks-mits-graduate-program-in-engineering-no-1-sloan-is-no-5-business-school-0311<p>MIT’s graduate program in engineering has been ranked No. 1 in the country in <i>U.S. News & World Report</i>’s annual rankings — a spot the Institute has held since 1990, when the magazine first ranked graduate programs in engineering.</p>
<p><i>U.S. News</i> awarded MIT a score of 100 among <a href="http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-engineering-schools" target="_blank">graduate programs in engineering,</a> followed by No. 2 Stanford University (93), No. 3 University of California at Berkeley (87), and No. 4 California Institute of Technology (80).</p>
<p>As was the case last year, MIT’s graduate programs led <i>U.S. News </i>lists in seven engineering disciplines. Top-ranked at MIT this year are programs in aerospace engineering; chemical engineering; materials engineering; computer engineering; electrical engineering (tied with Stanford and Berkeley); mechanical engineering (tied with Stanford); and nuclear engineering (tied with the University of Michigan). MIT’s graduate program in biomedical engineering was also a top-five finisher, tying for third with the University of California at San Diego.</p>
<p>In <i>U.S. News</i>’ first evaluation of <a href="http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-science-schools" target="_blank">PhD programs in the sciences</a> since 2010, five MIT programs earned a No. 1 ranking: biological sciences (tied with Harvard University and Stanford); chemistry (tied with Caltech and Berkeley, and with a No. 1 ranking in the specialty of inorganic chemistry); computer science (tied with Carnegie Mellon University, Stanford, and Berkeley); mathematics (tied with Princeton University, and with a No. 1 ranking in the specialty of discrete mathematics and combinations); and physics. MIT’s graduate program in earth sciences was ranked No. 2.</p>
<p>The MIT Sloan School of Management ranked fifth this year among the nation’s <a href="http://grad-schools.usnews.rankingsandreviews.com/best-graduate-schools/top-business-schools" target="_blank">top business schools</a>, behind Harvard Business School, Stanford’s Graduate School of Business, the Wharton School at the University of Pennsylvania, and the Booth School of Business at the University of Chicago.</p>
<p>Sloan’s graduate programs in information systems, production/operations, and supply chain/logistics were again ranked first this year; the Institute’s graduate offerings in entrepreneurship (No. 3) and finance (No. 5) also ranked among top-five programs.</p>
<p><i>U.S. News</i> does not issue annual rankings for all doctoral programs, but revisits many every few years. In the magazine’s 2013 evaluation of graduate programs in economics, MIT tied for first place with Harvard, Princeton, and Chicago.</p>
<p><i>U.S. News</i> bases its rankings of graduate schools of engineering and business on two types of data: reputational surveys of deans and other academic officials, and statistical indicators that measure the quality of a school’s faculty, research, and students. The magazine’s less-frequent rankings of programs in the sciences, social sciences, and humanities are based solely on reputational surveys.</p>
Rankings, Aeronautical and astronautical engineering, Biology, Biomedical engineering, Business and management, Computer science and technology, Education, teaching, academics, Electrical engineering and computer science, Graduate, postdoctoral, Materials science, Materials Science and Engineering, Mathematics, Mechanical engineering, Nuclear science and engineering, PhysicsNew algorithm can dramatically streamline solutions to the ‘max flow’ problem
http://news.mit.edu/2013/new-algorithm-can-dramatically-streamline-solutions-to-the-max-flow-problem-0107
Research could boost the efficiency even of huge networks like the Internet.Tue, 07 Jan 2014 05:00:04 -0500Helen Knight, MIT News correspondenthttp://news.mit.edu/2013/new-algorithm-can-dramatically-streamline-solutions-to-the-max-flow-problem-0107<p>Finding the most efficient way to transport items across a network like the U.S. highway system or the Internet is a problem that has taxed mathematicians and computer scientists for decades.<br />
<br />
To tackle the problem, researchers have traditionally used a maximum-flow algorithm, also known as “max flow,” in which a network is represented as a graph with a series of nodes, known as vertices, and connecting lines between them, called edges.<br />
<br />
Given that each edge has a maximum capacity — just like the roads or the fiber-optic cables used to transmit information around the Internet — such algorithms attempt to find the most efficient way to send goods from one node in the graph to another, without exceeding these constraints.<br />
<br />
But as the size of networks like the Internet has grown exponentially, it is often prohibitively time-consuming to solve these problems using traditional computing techniques, according to Jonathan Kelner, an associate professor of applied mathematics at MIT and a member of MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).<br />
<br />
So in a paper to be presented at the ACM-SIAM Symposium on Discrete Algorithms in Portland, Ore., this week, Kelner and his colleague Lorenzo Orecchia, an applied mathematics instructor, alongside graduate students Yin Tat Lee and Aaron Sidford, will describe a new theoretical algorithm that can dramatically reduce the number of operations needed to solve the max-flow problem, making it possible to tackle even huge networks like the Internet or the human genome.<br />
<br />
“There has recently been an explosion in the sizes of graphs being studied,” Kelner says. “For example, if you wanted to route traffic on the Internet, study all the connections on Facebook, or analyze genomic data, you could easily end up with graphs with millions, billions or even trillions of edges.”<br />
<br />
Previous max-flow algorithms have come at the problem one edge, or path, at a time, Kelner says. So for example, when sending items from node A to node B, the algorithms would transmit some of the goods down one path, until they reached its maximum capacity, and then begin sending some down the next path.<br />
<br />
“Many previous algorithms,” Kelner says, “would find a path from point A to point B, send some flow along it, and then say, ‘Given what I’ve already done, can I find another path along which I can send more?’ When one needs to send flow simultaneously along many different paths, this leads to an intrinsic limitation on the speed of the algorithm.”<br />
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But in 2011 Kelner, CSAIL graduate student Aleksander Madry, mathematics undergraduate Paul Christiano, and colleagues at Yale University and the University of Southern California developed a technique to analyze all of the paths simultaneously.<br />
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The researchers viewed the graph as a collection of electrical resistors, and then imagined connecting a battery to node A and a ground to node B, and allowing the current to flow through the network. “Electrical current doesn’t pick just one path, it will send a little bit of current over every resistor on the network,” Kelner says. “So it probes the whole graph globally, studying many paths at the same time.”<br />
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This allowed the new algorithm to solve the max-flow problem substantially faster than previous attempts.<br />
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Now the MIT team has developed a technique to reduce the running time even further, making it possible to analyze even gigantic networks, Kelner says.<br />
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Unlike previous algorithms, which have viewed all the paths within a graph as equals, the new technique identifies those routes that create a bottleneck within the network. The team’s algorithm divides each graph into clusters of well-connected nodes, and the paths between them that create bottlenecks, Kelner says.<br />
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“Our algorithm figures out which parts of the graph can easily route what they need to, and which parts are the bottlenecks. This allows you to focus on the problem areas and the high-level structure, instead of spending a lot of time making unimportant decisions, which means you can use your time a lot more efficiently,” he says.<br />
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The result is an almost linear algorithm, Kelner says, meaning the amount of time it takes to solve a problem is very close to being directly proportional to the number of nodes on the network. So if the number of nodes on the graph is multiplied by 10, the amount of time would be multiplied by something very close to 10, as opposed to being multiplied by 100 or 1,000, he says. “This means that it scales essentially as well as you could hope for with the size of the input,” he says.<br />
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Shanghua Teng, a professor of computer science at the University of Southern California who was not involved in the latest paper, says it represents a major breakthrough in graph algorithms and optimization software.<br />
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“This paper, which is the winner of the best paper award at the [ACM-SIAM] conference, is a result of sustained efforts by Kelner and his colleagues in applying electrical flows to design efficient graph algorithms,” Teng says. “The paper contains an amazing array of technical contributions.”<br />
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The paper was posted alongside work by Jonah Sherman of the University of California at Berkeley, who has also developed an almost linear algorithm for solving the max-flow problem, using an alternative technique.</p>
Algorithms, Computer Science and Artificial Intelligence Laboratory (CSAIL), Electrical Engineering & Computer Science (eecs), Mathematics, Max-flowGetting a move on in math
http://news.mit.edu/2013/getting-a-move-on-in-math-1223
Marshall Scholar Kirin Sinha is motivating young women to pursue math through dance.Mon, 23 Dec 2013 05:00:00 -0500Jennifer Chu, MIT News Officehttp://news.mit.edu/2013/getting-a-move-on-in-math-1223<p>MIT senior Kirin Sinha was just 3 years old when she took her first dance class. Unlike other girls who sign up for tap dancing or ballet to channel a gregarious personality, Sinha, by her own account, was painfully shy, and dance was a way for her to come out of her shell.<br />
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She soon found that she didn’t mind the spotlight. That first dance class led to many more; in grade school, Sinha started performing competitively, and later professionally, in classical Indian dance. Around the same time, she also discovered another interest: math. In high school, she competed in state and national mathematics competitions — often as the only female in the top ranks.<br />
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“I was constantly asked the question, ‘Why doesn’t it ever bother you that you’re the only girl, or that guys don’t think it’s cool if you’re good at math?’” Sinha recalls. “And I never had a good answer.”<br />
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It wasn’t until she was at MIT that Sinha realized that her confidence in math came from an unlikely source: dance.<br />
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“[Dance] teaches you discipline, attention to detail, and creativity,” she says. “It gives you the confidence to stand up there and not apologize for anything you’re doing. And that’s something I thought was missing with girls in mathematics.”<br />
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Compelled by this connection, in 2012 Sinha founded SHINE, a program whose mission is Supporting, Harnessing, Inspiring, Nurturing, and Empowering middle school girls to learn math by building their confidence through dance. This past year, Sinha recruited 37 girls from middle schools in Boston and Cambridge, as well as mentors from MIT, to participate in eight-week sessions of dance routines and math puzzles. Reluctant at first, the girls soon showed tangible improvement, pulling their grades up from C’s to A’s. And, Sinha adds, they liked the challenge.<br />
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Now she plans to take the program abroad: Sinha was one of 34 students nationwide — and four at MIT — awarded Marshall Scholarships last month to pursue two years of graduate studies in the United Kingdom. Starting next fall, she will undertake two master’s degrees, in mathematics and in advanced computer science, at Cambridge University, and hopes to explore ways to integrate SHINE into the British educational system. <br />
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<strong>Ahead of the curve</strong><br />
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Sinha was born in Baltimore and spent most of her childhood in Bethesda, Md. She remembers coming home from school each day, eager to tackle the math problems her mother gave her for fun. By third grade, she was working out equations in algebra — a subject typically taught in eighth or ninth grade. Because of her accelerated learning, Sinha says she was able to appreciate what others often don’t see in mathematics.<br />
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“I believe the reason people fall out of math is because it takes a long time to realize how beautiful it is,” Sinha says. “It’s when you get into number theory and abstract algebra and group theory — that’s when things get deconstructed at such a fundamental level that people get really excited, that they’re discovering a truth or structure to the universe. And people often lose interest before that level because it’s not taught like that.”<br />
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In high school, Sinha placed in the top 10 in national mathematics competitions, and was the highest scoring female in her state’s American Mathematics Competition and the American Invitational Mathematics Examination. She also applied this drive to other subjects, graduating from high school in three years.<br />
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While she was in high school, teachers from various local schools approached Sinha with the same question: Could she come tutor girls in math? Particularly in middle school, the educators noticed, girls’ performance and interest in the subject waned. So Sinha tutored young women and gave motivational talks about pursuing careers in science.<br />
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“I don’t think girls have less ability in math — that’s absurd,” Sinha says. “I think the only reason girls do poorly is that in their head, they don’t want to be the one girl who’s doing well — they don’t want to stand out.”<br />
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<strong>Building perspectives</strong><br />
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After graduation, Sinha headed to MIT to pursue majors in theoretical mathematics and in electrical engineering and computer science and a minor in music. She was particularly drawn to the elegant architecture of pure math, a subject that required “moving piece by piece to string together something that works.”<br />
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But Sinha also made an effort to seek out different perspectives, particularly in applied math. During her time at MIT, she took on several internships at companies that looked for mathematical solutions to practical problems. At the investment firm Blackstone Group, Sinha was part of a team that developed mathematical models to analyze hedge fund portfolios and perform risk analysis. And at the New York startup ADAPTLY, she helped create models that analyze advertising for ways to increase visibility on social networking sites like Facebook and Twitter.<br />
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“Having different perspectives is almost like having different tools,” Sinha says. “It makes you a better problem-solver.”<br />
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In the summer before her sophomore year, Sinha lived in an Italian monastery for six weeks. She slept under a bell tower, waking to its clanging early each morning. Not knowing the language, she spent most days in silence, washing clothes by hand, without electricity or hot water. The spare lifestyle left plenty of room for reflection.<br />
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“Being able to spend meaningful time with yourself is a very difficult thing,” Sinha says. “It very much helped clarify what I wanted to do and why.”<br />
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<strong>Dancing through the pipeline</strong><br />
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Upon returning to MIT, Sinha quickly drew up a proposal that ultimately became SHINE. She obtained funding with help from MIT’s Public Service Center, and started reaching out to area schools for willing participants. Thinking back to her tutoring experiences, Sinha decided to target girls in sixth and seventh grade — a time when girls’ interest and performance in math severely drops off.<br />
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“I’m worried about the girls who think they can’t do math, honestly believe that, and don’t care,” Sinha says. “If you say to these girls, ‘Hey, do you want to do math after school,’ they’re going to roll their eyes at you and not say anything. It’s a challenging pool, but I think it’s the key demographic.”<br />
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As Sinha found, dance is an enticing hook to get these girls interested and receptive to challenges in math. This past year, she led two sessions of SHINE, with a total of 37 middle school girls. Each day, the girls learned dance routines and worked on math problems; Sinha sometimes found ways to combine the two in exercises of “kinesthetic learning.” For example, she would integrate a lesson on the Cartesian plane into a dance routine, asking girls to rotate on the dance floor by a given number of degrees — an illustration of the coordinate system.<br />
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“It may not feel like work or learning, but it’s actually being embedded in your brain much deeper than just doing millions of practice exercises,” Sinha says.<br />
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Sinha hopes to pursue an academic path, and one day become a professor. She recently worked with professor of mathematics Scott Sheffield on problems in decision theory, and is currently working with professor of applied mathematics John Bush on the wave behavior of water droplets.<br />
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She says that while her mentors have been supportive and encouraging, she has never had a female math professor.<br />
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“I think there need to be more women in that role to encourage more women to move that way,” Sinha says. “We’re losing many of them around middle school, and if you consider in college you might lose more, by the time we get to PhDs, we’re talking about a very small pool. By increasing that pipeline, I think we’re doing a huge service.”</p>
Kirin SinhaAwards, honors and fellowships, Profile, Electrical Engineering & Computer Science (eecs), Marshall scholarships, Mathematics, Student life, Students, Undergraduate