Study finds the risks of sharing health care data are low
Greater availability of de-identified patient health data would enable better treatments and diagnostics, the researchers say.
Learning on the edge
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.
Making each vote count
MIT PhD candidate Jacob Jaffe uses data science to identify and solve problems in election administration.
Investigating at the interface of data science and computing
Guy Bresler builds mathematical models to understand multifaceted, interdisciplinary engineering problems that have far-reaching applications.
Neurodegenerative disease can progress in newly identified patterns
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.
New program to support translational research in AI, data science, and machine learning
The MIT-Pillar AI Collective will cultivate prospective entrepreneurs and drive innovation.
Q&A: Global challenges surrounding the deployment of AI
Aleksander Madry, Asu Ozdaglar, and Luis Videgaray, co-chairs of the AI Policy Forum, discuss key issues facing the AI policy landscape today.
In-home wireless device tracks disease progression in Parkinson’s patients
By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
Empowering Cambridge youth through data activism
Mayor’s youth employment program brought local high schoolers to MIT this summer.
Visualizing migration stories
“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.
AI that can learn the patterns of human language
On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
Taking a magnifying glass to data center operations
Lincoln Laboratory Supercomputing Center dataset aims to accelerate AI research into managing and optimizing high-performance computing systems.
Using seismology for groundwater management
New research showcases a pilot application using seismometers to monitor groundwater aquifers in California.
Researchers discover major roadblock in alleviating network congestion
Algorithms designed to ensure multiple users share a network fairly can’t prevent some users from hogging all the bandwidth.
A technique to improve both fairness and accuracy in artificial intelligence
Methods that make a machine-learning model’s predictions more accurate overall can reduce accuracy for underrepresented subgroups. A new approach can help.