Estimating suicide risk from text
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
A new language-processing tool could help identify the highest-risk individuals from natural language, enabling swifter interventions.
Patricia and James Poitras ’63 provide fellowships for graduate students and postdocs who will shape the future of mental health research.
The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
The “CrysVCD” tool developed at MIT could cut the huge amounts of time and money spent on screening out chemically unstable designs.
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that’s essential to fertilizer and other products.
An expert in machine learning, statistics, and computation, Rakhlin succeeds Professor Ankur Moitra.
Initial research projects advance national priorities across natural resources, manufacturing, nuclear physics, and more.
The professor of physics and inaugural director of the NSF AI Institute for Artificial Intelligence and Fundamental Interactions will lead LNS and continue his research in particle physics.
PhD student Rachel Sava, winner of the Envisioning the Future of Computing Prize, explores transformative improvements and dystopian risks of neural technology.