Toward a future that preserves benefits of neurotechnology for all
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.
MIT researchers’ approach captures subtle atomic patterns, improving predictions of material properties.
The fellowships in applied sciences, engineering, and mathematics recognize doctoral students who are pursuing solutions to the most pressing challenges in science and technology.
IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.
Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.
The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.
Professor Jesse Thaler describes a vision for a two-way bridge between artificial intelligence and the mathematical and physical sciences — one that promises to advance both.
Industry leaders agree collaboration is key to advancing critical technologies.
Solubility predictions could make it easier to design and synthesize new drugs, while minimizing the use of more hazardous solvents.
ChemXploreML makes advanced chemical predictions easier and faster — without requiring deep programming skills.