The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
New research shows the natural variability in climate data can cause AI models to struggle at predicting local temperature and rainfall.
A new approach can reveal the features AI models use to predict proteins that might make good drug or vaccine targets.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
ChemXploreML makes advanced chemical predictions easier and faster — without requiring deep programming skills.
CellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
FutureHouse, co-founded by Sam Rodriques PhD ’19, has developed AI agents to automate key steps on the path toward scientific progress.
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.
The MIT-MGB Seed Program, launched with support from Analog Devices Inc., will fund joint research projects that advance technology and clinical research.
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
