NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery
IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics.
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.
CellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
Chemists could use this quick computational method to design more efficient reactions that yield useful compounds, from fuels to pharmaceuticals.
A new method lets users ask, in plain language, for a new molecule with certain properties, and receive a detailed description of how to synthesize it.