MIT Schwarzman College of Computing awards named professorships to two faculty members
Dina Katabi and Aleksander Madry receive additional support to pursue their research and develop their careers.
Dina Katabi and Aleksander Madry receive additional support to pursue their research and develop their careers.
MIT student Eeshan Tripathii is working with his sister to engineer an intuitive brain-controlled interface for upper-limb prosthetics.
An optimization tool from the Department of Air Force–MIT AI Accelerator is transforming the laborious process of staffing C-17 cargo flights.
MIT researchers train a neural network to predict a “boiling crisis,” with potential applications for cooling computer chips and nuclear reactors.
“This is a really exciting time to be a roboticist who also cares about the environment,” says PhD student Victoria Preston.
MIT alumnus-founded RightHand Robotics has developed picking robots that are more reliable and adaptable in warehouse environments.
Graduate student Ellen Zhong helped biologists and mathematicians reach across departmental lines to address a longstanding problem in electron microscopy.
Faculty from the departments of Physics and of Nuclear Science and Engineering faculty were selected for the Early Career Research Program.
Selective global honor supports early-career scientists and engineers in taking on new pursuits.
A new art/science collaboration uses molecular structures as its creative medium.
Nearly 300 government and military members participated in a new course designed to explore the next generation of artificial intelligence and related technologies.
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
Assistant professor Connor Coley is developing tools that would be able to predict molecular behavior and learn from both successes and mistakes.
How a pair of MIT Sloan Executive Education alumni translated teachings from an MIT course to operations improvements at Mexico’s largest brewery.
Math professor Ankur Moitra seeks algorithms with provable guarantees, to pin down the mechanisms of machine learning.