Anantha Chandrakasan named MIT provost
A faculty member since 1994, Chandrakasan has also served as dean of engineering and MIT’s inaugural chief innovation and strategy officer, among other roles.
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A faculty member since 1994, Chandrakasan has also served as dean of engineering and MIT’s inaugural chief innovation and strategy officer, among other roles.
Protein sensor developed by alumna-founded Advanced Silicon Group can be used for research and quality control in biomanufacturing.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.
The system automatically learns to adapt to unknown disturbances such as gusting winds.
The winning essay of the Envisioning the Future of Computing Prize puts health care disparities at the forefront.
Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.
The approach could help animators to create realistic 3D characters or engineers to design elastic products.
Researchers developed an algorithm that lets a robot “think ahead” and consider thousands of potential motion plans simultaneously.
A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.
In an annual tradition, MIT affiliates embarked on a trip to Washington to explore federal lawmaking and advocate for science policy.
SketchAgent, a drawing system developed by MIT CSAIL researchers, sketches up concepts stroke-by-stroke, teaching language models to visually express concepts on their own and collaborate with humans.
The fellowships recognize doctoral students who have “the extraordinary creativity and principled leadership necessary to tackle problems others can’t solve.”
PhD student Sarah Alnegheimish wants to make machine learning systems accessible.
This new machine-learning model can match corresponding audio and visual data, which could someday help robots interact in the real world.