Building AI models that understand chemical principles
Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.
Connor Coley works at the interface of chemistry and machine learning, to discover and design new drug compounds.
MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.
The prestigious fellowship funds graduate studies at Stanford University.
Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.
Building on a long-standing MIT–IBM collaboration, the new lab will chart the convergence of AI, algorithms, and quantum computing.
A new method could bring more accurate and efficient AI models to high-stakes applications like health care and finance, even in under-resourced settings.
The “EnergAIzer” method generates reliable results in seconds, enabling data center operators to efficiently allocate resources and reduce wasted energy.
New dataset of 30,000-plus competition math problems from 47 countries gives AI researchers a harder test — and students worldwide a better training ground.
A new training method improves the reliability of AI confidence estimates without sacrificing performance, addressing a root cause of hallucination in reasoning models.
The associate professors of EECS and chemistry, respectively, are honored for exceptional contributions to teaching, research, and service at MIT.