MIT Schwarzman College of Computing

The MIT Class of 2020 can look forward to an online celebration that Professor Eric Grimson, chair of the Commencement Committee, calls, "a joyful day that will honor our graduates."

Hacking Commencement

Marshalling forces from across the Institute, MIT will deliver an online celebration worthy of the Class of 2020.

May 26, 2020

Students participating in MIT Quest for Intelligence-funded UROP projects include: (clockwise from top left) Alon Kosowsky-Sachs, Isaac Wolverton, Kuan Wei Huang, and Karen Gu.

Undergraduates develop next-generation intelligence tools

UROP students explore applications in robotics, health care, language understanding, and nuclear engineering.

May 26, 2020

Microsoft President Brad Smith’s conversation with MIT Professor Daniela Rus on May 14 spanned a wide range of topics, from the challenges of Covid-19 to the security of online voting. The event was held as part of MIT’s “Hot Topics in Computing” series.

Microsoft President Brad Smith talks data, Covid-19, and a potential “digital 9/11”

Smith spoke with CSAIL Director Daniela Rus as part of a special series co-presented by the MIT Schwarzman College of Computing.

May 21, 2020

White blood cells are among the first to mount an attack against sepsis, a deadly complication of Covid-19. In a project led by MIT Professor Daniela Rus, researchers are developing a machine learning system to detect an activated immune response to sepsis which could lead to earlier, more aggressive treatment. Here, a white blood cell attacks malaria.

Marshaling artificial intelligence in the fight against Covid-19

The MIT-IBM Watson AI Lab is funding 10 research projects aimed at addressing the health and economic consequences of the pandemic.

May 19, 2020

Sapple, a system developed at the MIT Computer Science and Artificial Intelligence Laboratory, analyzes in-home appliance usage to better understand health patterns, using just radio signals and a smart electricity meter.

What can your microwave tell you about your health?

An MIT system uses wireless signals to measure in-home appliance usage to better understand health tendencies.

May 18, 2020

Researchers with the IDSS Covid-19 Collaboration (Isolat) are designing a control model for testing and isolating members of communities like MIT’s to reduce Covid-19 infection.

A data-driven response to a pandemic

Isolat, a volunteer collaboration organized by the Institute for Data, Systems, and Society, informs coronavirus policy by analyzing data associated with the pandemic.

May 15, 2020

“The foundation for teaching ethics at MIT is for students to have a sense of proximity to social and ethical issues,” says Milo Phillips-Brown, a postdoc in philosophy. “The idea of having this class be so student-driven is that this allows them to come to ethics on their own terms; they follow what’s important to them and develop an inner motivation to be involved.”

Infusing ethics into experiential learning

In a new undergraduate course, students explore the ethical dimensions of their experiences.

May 8, 2020

MIT researchers have developed a kind of creativity test for generative models to see how far they can go in visualizing objects in photos from various angles and in different colors. The tool shows how much the model's imagination depends on the variety of images it has seen.

Visualizing the world beyond the frame

Researchers test how far artificial intelligence models can go in dreaming up varied poses and colors of objects and animals in photos.

May 6, 2020

MIT researchers have proposed a technique for shrinking deep learning models that they say is simpler and produces more accurate results than state-of-the-art methods. It works by retraining the smaller, pruned model at its faster, initial learning rate.

A foolproof way to shrink deep learning models

Researchers unveil a pruning algorithm to make artificial intelligence applications run faster.

April 30, 2020

MIT researchers used machine learning to find entirely new algorithms for encoding exploration. Their machine-designed algorithms outperformed human-designed algorithms on the wide range of simulated tasks and environments shown here.

Automating the search for entirely new “curiosity” algorithms

Researchers show that computers can “write” algorithms that adapt to radically different environments better than algorithms designed by humans.

April 28, 2020

Mathai Mammen, head of R&D at the Janssen Pharmaceutical Companies of Johnson & Johnson, was the keynote speaker at the Jameel Clinic's AI Powered Drug Discovery and Manufacturing Conference in February.

MIT conference reveals the power of using artificial intelligence to discover new drugs

Inaugural AI Powered Drug Discovery and Manufacturing Conference drew pharmaceutical companies, government regulators, and pioneering drug researchers.

April 27, 2020

Lead author Joseph DelPreto controls a "Conduct-A-Bot" drone with his arm muscles.

Muscle signals can pilot a robot

CSAIL's Conduct-A-Bot system uses muscle signals to cue a drone’s movement, enabling more natural human-robot communication.

April 27, 2020

A new hospital status app aims to balance hospitals’ Covid-19 load. Based on crowdsourced data, the app gives patients, EMTs, and physicians tools to report and check on availability of hospital resources, from ventilators and ICU beds to average wait times.

Reporting tool aims to balance hospitals’ Covid-19 load

Based on crowdsourced data, app helps patients, EMTs, and physicians determine real-time availability of hospital resources.

April 23, 2020

Marija Ilic — a senior research scientist at the Laboratory for Information and Decision Systems, affiliate of the MIT Institute for Data, Systems, and Society, senior staff in MIT Lincoln Laboratory’s Energy Systems Group, and Carnegie Mellon University professor emerita — is a researcher on a mission: making electric energy systems future-ready.

Shedding light on complex power systems

Senior Research Scientist Marija Ilic is making electric energy systems future-ready.

April 23, 2020

MIT researchers have developed a new automated AI system with improved computational efficiency and a much smaller carbon footprint. The researchers’ system trains one large neural network comprising many pretrained subnetworks of different sizes that can be tailored to diverse hardware platforms without retraining.

Reducing the carbon footprint of artificial intelligence

MIT system cuts the energy required for training and running neural networks.

April 23, 2020

MIT News | Massachusetts Institute of Technology

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Hacking Commencement

Undergraduates develop next-generation intelligence tools

Microsoft President Brad Smith talks data, Covid-19, and a potential “digital 9/11”

Marshaling artificial intelligence in the fight against Covid-19

What can your microwave tell you about your health?

A data-driven response to a pandemic

Infusing ethics into experiential learning

Visualizing the world beyond the frame

A foolproof way to shrink deep learning models

Automating the search for entirely new “curiosity” algorithms

MIT conference reveals the power of using artificial intelligence to discover new drugs

Muscle signals can pilot a robot

Reporting tool aims to balance hospitals’ Covid-19 load

Shedding light on complex power systems

Reducing the carbon footprint of artificial intelligence

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MIT Schwarzman College of Computing