Following the questions where they lead
Assistant Professor Bailey Flanigan has arrived at complex computational methods for helping democracy thrive.
Dimitri Bertsekas, Prolific Author in Optimization, Dynamic Programming and Reinforcement Learning, Dies at 83.
Bertsekas’s research spanned, and had a major influence upon, several fields, including optimization, control, large-scale computation, reinforcement learning, and artificial intelligence.
Helping AI models to meet the real world
Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.
Tiny robot boats build floating structures
MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.
“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.
Researchers found a simple solution for extending the lifespans of LEDs made from glowing microscopic particles called quantum dots.
A recent Reunion activity, taught by EECS Senior Lecturer Gim Hom, doubled as both his “last class” and a chance to reconnect with classmates.
Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.
A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.
Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.