At the core of problem-solving
Stuart Levine ’97, director of MIT’s BioMicro Center, keeps departmental researchers at the forefront of systems biology.
Topic
Computer Science and Artificial Intelligence Laboratory (CSAIL)
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3D printing approach strings together dynamic objects for you
“Xstrings” method enables users to produce cable-driven objects, automatically assembling bionic robots, sculptures, and dynamic fashion designs.
High-performance computing, with much less code
The Exo 2 programming language enables reusable scheduling libraries external to compilers.
Robotic helper making mistakes? Just nudge it in the right direction
New research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
Letterlocking: A new look at a centuries-old practice
A first history of the document security technology, co-authored by MIT Libraries’ Jana Dambrogio, provides new tools for interdisciplinary research.
MIT faculty, alumni named 2025 Sloan Research Fellows
Annual award honors early-career researchers for creativity, innovation, and research accomplishments.
Like human brains, large language models reason about diverse data in a general way
A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.
AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
To keep hardware safe, cut out the code’s clues
New “Oreo” method from MIT CSAIL researchers removes footprints that reveal where code is stored before a hacker can see them.
Creating a common language
New faculty member Kaiming He discusses AI’s role in lowering barriers between scientific fields and fostering collaboration across scientific disciplines.
Validation technique could help scientists make more accurate forecasts
MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.
Introducing the MIT Generative AI Impact Consortium
The consortium will bring researchers and industry together to focus on impact.
User-friendly system can help developers build more efficient simulations and AI models
By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.
3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
Toward video generative models of the molecular world
Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.