MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

MIT Schwarzman College of Computing

Artificial Intelligence Civil and environmental engineering Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing Research Robotics Safety School of Engineering

New control system teaches soft robots the art of staying safe

MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.

Artificial Intelligence Center for International Studies Classes and programs Collaboration Data Environment Europe Food Global Industry International initiatives Internships machine learning Mechanical engineering MISTI MIT Schwarzman College of Computing MIT Sea Grant Oceanography and ocean engineering Robotics School of Engineering School of Humanities Arts and Social Sciences sensors Software Students UAV Undergraduate Undergraduate Research Opportunities Program (UROP) Water

MIT Sea Grant students explore the intersection of technology and offshore aquaculture in Norway

AquaCulture Shock program, in collaboration with MIT-Scandinavia MISTI, offers international internships for AI and autonomy in aquaculture

Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and society

Researchers discover a shortcoming that makes LLMs less reliable

Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Drug development Electrical engineering and computer science (EECS) Health sciences and technology Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing Pharmaceuticals Proteins Research School of Engineering Special events and guest speakers

MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

BoltzGen generates protein binders for any biological target from scratch, expanding AI’s reach from understanding biology toward engineering it.

Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Faculty machine learning MIT Schwarzman College of Computing Profile School of Engineering

Understanding the nuances of human-like intelligence

Associate Professor Phillip Isola studies the ways in which intelligent machines “think,” in an effort to safely integrate AI into human society.

Algorithms Artificial Intelligence Classes and programs Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Graduate, postdoctoral Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering Students

Charting the future of AI, from safer answers to faster thinking

MIT PhD students who interned with the MIT-IBM Watson AI Lab Summer Program are pushing AI tools to be more flexible, efficient, and grounded in truth.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Programming Programming languages Research School of Engineering Software

MIT researchers propose a new model for legible, modular software

The coding framework uses modular concepts and simple synchronization rules to make software clearer, safer, and easier for LLMs to generate.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles Computer science and technology computer-vision Disaster response Electrical engineering and computer science (EECS) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research Robotics School of Engineering

Teaching robots to map large environments

A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Graduate, postdoctoral Interview machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Pollution Research School of Engineering Students Sustainability

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.

Algorithms Alternative energy Artificial Intelligence Computer science and technology Electrical engineering and computer science (EECS) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

A faster problem-solving tool that guarantees feasibility

The FSNet system, developed at MIT, could help power grid operators rapidly find feasible solutions for optimizing the flow of electricity.