Achieving greater efficiency for fast data center operations
System better allocates time-sensitive data processing across cores to maintain quick user-response times.
System better allocates time-sensitive data processing across cores to maintain quick user-response times.
Undergraduate research projects show how students are advancing research in human and artificial intelligence, and applying intelligence tools to other disciplines.
New platform forces data center servers to only use data in ways that users explicitly approve.
Researchers have devised a faster, more efficient way to design custom peptides and perturb protein-protein interactions.
An algorithm that teaches robot agents how to exchange advice to complete a task helps them learn faster.
Neural network assimilates multiple types of health data to help doctors make decisions with incomplete information.
Health Analytics Collective uses real-world evidence to modernize health and drug development decisions.
Model identifies instances when autonomous systems have learned from examples that may cause dangerous errors in the real world.
MIT “Policy Congress” examines the complex terrain of artificial intelligence regulation.
Hackathons promote doctor-data scientist collaboration and expanded access to electronic medical-records to improve patient care.
Tool for nonstatisticians automatically generates models that glean insights from complex datasets.
New EAPS thesis field is the most recent to join the computational science and engineering doctoral program within the Center for Computational Engineering.
“Counterpoints,” produced by MIT Sloan Management Review, aims to reveal fascinating insights about sports analytics.
Merging different types of location-stamped data can make it easier to discern users’ identities, even when the data is anonymized.