Adam Petway, strength and conditioning coach for the University of Louisville, is using his MIT Professional Education training to improve player performance off the court.
Greater availability of de-identified patient health data would enable better treatments and diagnostics, the researchers say.
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.
MIT PhD candidate Jacob Jaffe uses data science to identify and solve problems in election administration.
Guy Bresler builds mathematical models to understand multifaceted, interdisciplinary engineering problems that have far-reaching applications.
A machine-learning method finds patterns of health decline in ALS, informing future clinical trial designs and mechanism discovery. The technique also extends to Alzheimer’s and Parkinson’s.
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.
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
Mayor’s youth employment program brought local high schoolers to MIT this summer.
“Distance Unknown,” an exhibition by MIT’s Civic Data Design Lab, documents the often challenging journeys migrants undertake to gain economic opportunity and food security.
On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
Lincoln Laboratory Supercomputing Center dataset aims to accelerate AI research into managing and optimizing high-performance computing systems.
New research showcases a pilot application using seismometers to monitor groundwater aquifers in California.
Algorithms designed to ensure multiple users share a network fairly can’t prevent some users from hogging all the bandwidth.