MIT system “sees” the inner structure of the body during physical rehab
A system for monitoring motion and muscle engagement could aid the elderly and athletes during unsupervised physical rehabilitation for injuries or impaired mobility.
A system for monitoring motion and muscle engagement could aid the elderly and athletes during unsupervised physical rehabilitation for injuries or impaired mobility.
MMIP aims to incentivize more students to consider a career in semiconductors and microelectronics, addressing a crucial, nationwide talent gap.
Awards support high-risk, high-impact research from early-career investigators.
A new study maps the genes and cellular pathways that contribute to exercise-induced weight loss.
A new technique enables AI models to continually learn from new data on intelligent edge devices like smartphones and sensors, reducing energy costs and privacy risks.
Guy Bresler builds mathematical models to understand multifaceted, interdisciplinary engineering problems that have far-reaching applications.
The MIT-Pillar AI Collective will cultivate prospective entrepreneurs and drive innovation.
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
The device could help scientists explore unknown regions of the ocean, track pollution, or monitor the effects of climate change.
Researchers created a system that lets robots effectively use grasped tools with the correct amount of force.
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
Throughout his career, Professor Hal Abelson has worked to make information technology more accessible to people of all ages.
The MIT Schwarzman College of Computing welcomes four new faculty members engaged in research and teaching that address climate risks and other environmental issues.
Researchers develop a new method that uses multiple models to create more complex images with better understanding.
Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.