(PINNs) – Physics Informed Neural Networks: Algorithms, Theory, and Applications

(PINNs) – Physics Informed Neural Networks: Algorithms, Theory, and Applications, MSML2020 Invited Talk by Prof. George Karniadakis, Brown University

Universal AI is “a pathway to AI fluency that’s accessible and approachable to anyone, anywhere” 12/05/2026

New AI education program from MIT Open Learning debuts with AI-powered personalization and a free introductory course for learners everywhere.

Carolyn Tiernan | MIT Open Learning

Games people — and machines — play: Untangling strategic reasoning to advance AI 05/05/2026

Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.

Michaela Jarvis | MIT Laboratory for Information and Decision Systems

Beacon Biosignals is mapping the brain during sleep 01/05/2026

Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.

Zach Winn | MIT News

MIT BrainTrust supports neighbors living with brain injuries 06/05/2026

Nearly 100 MIT students participate in a buddy program that assists Boston-area residents.

Sarah Foote | Division of Student Life

Biologist Joey Davis explores how cells build complex structures 05/05/2026

His studies have shed light on the assembly instructions that govern ribosomes, the critical protein-building machines of the cell.

Anne Trafton | MIT News

Rett syndrome study highlights potential for personalized treatments 04/05/2026

Using advanced human cell cultures, MIT researchers tracked how two different mutations alter neural circuit development, and how each could be addressed with distinct potential therapeutics.

David Orenstein | The Picower Institute for Learning and Memory