Behrooz Tahmasebi — an MIT PhD student in the Department of Electrical Engineering and Computer Science (EECS) and an affiliate of the Computer Science and Artificial Intelligence Laboratory (CSAIL) — was taking a mathematics course on differential equations in late 2021 when a glimmer of inspiration struck.
Hundreds of participants from around the world joined the sixth annual MIT Policy Hackathon to develop data-informed policy solutions to challenges in health, housing, and more.
The 2024 Symposium will be hosted on April 30th by MIT MIMO in collaboration with MIT CSAIL at MIT’s Wong Auditorium. Hear from Professor Wojciech Matusik during the event.
CSAIL Alliances members receive 20% off registration with the code below.
Like many of us, you might find yourself nodding to a familiar digital doomsday chorus that vibrates through offices and coffee shops alike: AI will take my job!
The first documented case of pancreatic cancer dates back to the 18th century. Since then, researchers have undertaken a protracted and challenging odyssey to understand the elusive and deadly disease. To date, there is no better cancer treatment than early intervention. Unfortunately, the pancreas, nestled deep within the abdomen, is particularly elusive for early detection.
An interdisciplinary team of researchers thinks health AI could benefit from some of the aviation industry’s long history of hard-won lessons that have created one of the safest activities today.
MIT’s Improbable AI Lab, a group within CSAIL, has offered these machines a helping hand with a new multimodal framework: Compositional Foundation Models for Hierarchical Planning (HiP), which develops detailed, feasible plans with the expertise of three different foundation models.
MIT researchers propose “PEDS” method for developing models of complex physical systems in mechanics, optics, thermal transport, fluid dynamics, physical chemistry, climate, and more.
