School of Science
School of Science

School of Science

Administration Algorithms Artificial Intelligence Community Computer science and technology Electrical Engineering & Computer Science (eecs) Faculty Funding Grants machine learning MIT Schwarzman College of Computing President Sally Kornbluth Provost Research School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science Technology and policy Technology and society

MIT scholars awarded seed grants to probe the social implications of generative AI

The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.

Alternative energy Artificial Intelligence Collaboration Data Department of Energy (DoE) Diversity and inclusion Energy Funding Fusion machine learning Nuclear science and engineering open source Physics Plasma Science and Fusion Center Renewable energy Research School of Engineering School of Science Software Women in STEM

Fast-tracking fusion energy’s arrival with AI and accessibility

MIT Plasma Science and Fusion Center will receive DoE support to improve access to fusion data and increase workforce diversity.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Collaboration Comparative Media Studies/Writing Computer Science and Artificial Intelligence Laboratory (CSAIL) Data Economics Electrical Engineering & Computer Science (eecs) Funding Grants Human-computer interaction Industry Laboratory for Information and Decision Systems (LIDS) machine learning Media Lab MIT Schwarzman College of Computing MIT Sloan School of Management Operations research Physics Research School of Engineering School of Humanities Arts and Social Sciences School of Science Technology and society

Artificial intelligence for augmentation and productivity

The MIT Schwarzman College of Computing awards seed grants to seven interdisciplinary projects exploring AI-augmented management.

Artificial Intelligence Brain and cognitive sciences Cells Computer science and technology machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Institutes of Health (NIH) Neuroscience Research School of Science

AI models are powerful, but are they biologically plausible?

A new study bridging neuroscience and machine learning offers insights into the potential role of astrocytes in the human brain.

Artificial Intelligence Brain and cognitive sciences Computer modeling computer-vision McGovern Institute MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Neuroscience Quest for Intelligence Research School of Engineering School of Science

When computer vision works more like a brain, it sees more like people do

Training artificial neural networks with data from real brains can make computer vision more robust.

Artificial Intelligence Arts Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering School of Science

Computer vision system marries image recognition and generation

MAGE merges the two key tasks of image generation and recognition, typically trained separately, into a single system.

Artificial Intelligence Awards, honors and fellowships Brain and cognitive sciences Computer science and technology Contests and academic competitions Electrical Engineering & Computer Science (eecs) Graduate, postdoctoral Human-computer interaction Management Mathematics Media Lab MIT Schwarzman College of Computing MIT Sloan School of Management Philosophy School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science Students Technology and policy Technology and society Undergraduate Urban studies and planning

Envisioning the future of computing

MIT students share ideas, aspirations, and vision for how advances in computing stand to transform society in a competition hosted by the Social and Ethical Responsibilities of Computing.

Artificial Intelligence Astronomy Astrophysics Awards, honors and fellowships Graduate, postdoctoral Physics Quantum Computing Quantum mechanics School of Science Space, astronomy and planetary science Spain Staff

Three Spanish MIT physics postdocs receive Botton Foundation fellowships

Recipients Luis Antonio Benítez, Carolina Cuesta-Lazaro, and Fernando Romero López receive support for their scientific research.

Algorithms Anthropology Artificial Intelligence Augmented and virtual reality Biology Brain and cognitive sciences Business and management Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Economics Education, teaching, academics Electrical Engineering & Computer Science (eecs) Ethics Faculty Government Graduate, postdoctoral Health Care Humanities IDSS Industry machine learning Mathematics MIT Schwarzman College of Computing MIT Sloan School of Management Political science Program in STS Research School of Architecture and Planning School of Engineering School of Humanities Arts and Social Sciences School of Science social media Special events and guest speakers Students Technology and policy Technology and society Undergraduate Urban studies and planning

Bringing the social and ethical responsibilities of computing to the forefront

The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.

Artificial Intelligence Biological engineering Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Drug discovery Electrical engineering and computer science (EECS) machine learning Mathematics MIT Schwarzman College of Computing National Institutes of Health (NIH) National Science Foundation (NSF) Proteins Ragon Institute Research School of Engineering School of Science

New model offers a way to speed up drug discovery

By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.