New model predicts how mosquitoes will fly A new 3D model reveals how mosquitoes adjust their flight patterns in response to visual and chemical cues. The research could help in the design of more effective traps and mosquito control strategie...

Researchers at MIT and Georgia Tech, including MathWorks Professor of Mathematics Jörn Dunkel, devised a new model predicting how mosquitoes will fly.

Read more at MIT News: news.mit.edu/2026/new-mod...

Exposing biases, moods, personalities, and abstract concepts hidden in large language models A new method can test whether a large language model contains hidden biases, personalities, moods, or other abstract concepts. MIT researchers can zero in on connections within a model that encode for...

A team from MIT and UCSD including Assistant Professor Adityanarayanan "Adit" Radhakrishnan have devised a way to test whether LLMs hold hidden biases, moods, and abstract concepts, marking a major step towards creating models which are safe yet effective.

news.mit.edu/2026/exposin... (MIT News)

MIT Alum Awarded 2025 MacArthur “Genius Grant” MIT alumna and mathematician Lauren K. Williams PhD ’05 has won a 2025 MacArthur Fellowship.Read more.

Lauren K. Williams PhD ‘05 has been named a 2025 MacArthur Fellow for "significant contributions to numerous mathematical fields, including cluster algebras, representation theory, and algebraic geometry.”

👉 Read more via MIT Alumni:
alum.mit.edu/slice/mit-al...

Researchers glimpse the inner workings of protein language models MIT researchers used sparse autoencoders to shed light on the inner workings of protein language models, an advance that could streamline the process of identifying new drugs or vaccine targets.

By using a sparse autoencoder, Prof Berger and
@bergerlab.bsky.social students uncover how protein language models make predictions."Identifying features that protein language models track has the potential to reveal novel biological insights from these representations." @mitscience.bsky.social