Professor Emeritus Sanjoy Mitter, expert in the theoretical foundations of systems, communication, and control, dies at 89
The former director of LIDS was a beloved professor who blended intellectual rigor with curiosity.
The former director of LIDS was a beloved professor who blended intellectual rigor with curiosity.
Predictions from the OncoNPC model could enable doctors to choose targeted treatments for difficult-to-treat tumors.
With a new, user-friendly interface, researchers can quickly design many cellular metamaterial structures that have unique mechanical properties.
“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.
Faculty and researchers across MIT’s School of Engineering receive many awards in recognition of their scholarship, service, and overall excellence.
The founders of MIT spinout Active Surfaces describe their thin-film solar technology and their experience winning this year’s $100K.
The device detects the same molecules that cell receptors do, and may enable routine early screening for cancers and other diseases.
A new technique helps a nontechnical user understand why a robot failed, and then fine-tune it with minimal effort to perform a task effectively.
EECS professor appointed to new professorship in the MIT Schwarzman College of Computing.
PIGINet leverages machine learning to streamline and enhance household robots' task and motion planning, by assessing and filtering feasible solutions in complex environments.
Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.
“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
Prestigious awards recognize community support of MIT’s goals, values, and mission.
PhD student Will Sussman studies wireless networks while fostering community networks.
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.