Researchers glimpse the inner workings of protein language models
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.
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School of Science
MIT tool visualizes and edits “physically impossible” objects
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
Read MoreNew machine-learning application to help researchers predict chemical properties
ChemXploreML makes advanced chemical predictions easier and faster — without requiring deep programming skills.
Read MoreCellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
Read MoreFutureHouse, co-founded by Sam Rodriques PhD ’19, has developed AI agents to automate key steps on the path toward scientific progress.
Read MoreThe MIT-MGB Seed Program, launched with support from Analog Devices Inc., will fund joint research projects that advance technology and clinical research.
Read MoreUsing generative AI to help robots jump higher and land safely
MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.
Read MorePresentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Read MoreA sounding board for strengthening the student experience
Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.
Read MoreBringing meaning into technology deployment
The MIT Ethics of Computing Research Symposium showcases projects at the intersection of technology, ethics, and social responsibility.
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