MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

A new model measures defects that can be leveraged to improve materials’ mechanical strength, heat transfer, and energy-conversion efficiency.

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.

This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.

With this new technique, a robot could more accurately detect hidden objects or understand an indoor scene using reflected Wi-Fi signals.

Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.

Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.

Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.

A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.

Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.