MIT affiliates named 2026 Schmidt Sciences AI2050 Fellows
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
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Biology
AI model decodes the language cells use to communicate
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Read MoreMIT Quantum Initiative launches postdoctoral fellowship program
The Institute welcomes its first cohort of QMIT Fellows this fall to advance interdisciplinary quantum research.
Read MoreLooking beyond natural sequences
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.
Read MoreMIT engineers design proteins by their motion, not just their shape
An AI model generates novel proteins based on how they vibrate and move, opening new possibilities for dynamic biomaterials and adaptive therapeutics.
Read More3 Questions: Building predictive models to characterize tumor progression
Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.
Read MoreAI to help researchers see the bigger picture in cell biology
By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.
Read MoreKatie Spivakovsky wins 2026 Churchill Scholarship
The MIT senior will pursue a master’s degree at Cambridge University in the U.K. this fall.
Read More3 Questions: Using computation to study the world’s best single-celled chemists
Assistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.
Read MoreDeep-learning model predicts how fruit flies form, cell by cell
The approach could apply to more complex tissues and organs, helping researchers to identify early signs of disease.
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