Electrical engineering and computer science (EECS)
Electrical engineering and computer science (EECS)

New algorithms enable efficient machine learning with symmetric data

This new approach could lead to enhanced AI models for drug and materials discovery.

“FUTURE PHASES” showcases new frontiers in music technology and interactive performance

Groundbreaking MIT concert, featuring electronic and computer-generated music, was a part of the 2025 International Computer Music Conference.

Robot, know thyself: New vision-based system teaches machines to understand their bodies

Neural Jacobian Fields, developed by MIT CSAIL researchers, can learn to control any robot from a single camera, without any other sensors.

A new way to edit or generate images

MIT researchers found that special kinds of neural networks, called encoders or “tokenizers,” can do much more than previously realized.

The unique, mathematical shortcuts language models use to predict dynamic scenarios

Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.

Can AI really code? Study maps the roadblocks to autonomous software engineering

A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.

How to more efficiently study complex treatment interactions

A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.

Changing the conversation in health care

The Language/AI Incubator, an MIT Human Insight Collaborative project, is investigating how AI can improve communications among patients and practitioners.

AI shapes autonomous underwater “gliders”

An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data.

Study could lead to LLMs that are better at complex reasoning

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.