(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

New AI technique could make minimally invasive surgeries safer and more precise 16/09/2026

This patient-specific method, called xvr, helps doctors use X-rays for surgical navigation in fields such as orthopedics and neurosurgery.

Adam Zewe | MIT News

New method enables AI for safety-critical situations 14/09/2026

The “HardFlow” algorithm could help generative AI models produce high-quality outputs that obey strict requirements when “pretty close” doesn’t cut it.

Adam Zewe | MIT News

MIT Schwarzman College of Computing launches pilot to help educators teach AI across disciplines 09/09/2026

A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.

Amanda Diehl | MIT Schwarzman College of Computing

Atlas of the brain’s striatum could guide researchers to new drug treatments 01/09/2026

A new study reveals insights into populations of neurons affected by Huntington’s disease, schizophrenia, addiction, and other disorders.

Anne Trafton | MIT News

MIT Quantum Initiative launches postdoctoral fellowship program 31/08/2026

The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.

Liam McDonnell | Office of Innovation and Strategy

Study: Peptides can form well-defined structures in harsh, Venus-like conditions 31/08/2026

New research offers support for the possibility that complex biological molecules could exist in the highly acidic environment of Venus’s cloud layer.

Anne Trafton | MIT News