A faster problem-solving tool that guarantees feasibility
The FSNet system, developed at MIT, could help power grid operators rapidly find feasible solutions for optimizing the flow of electricity.
MIT Schwarzman College of Computing
Five with MIT ties elected to National Academy of Medicine for 2025
Professors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.
Read MoreCreating AI that matters
How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.
Read MoreNew software designs eco-friendly clothing that can reassemble into new items
To reduce waste, the Refashion program helps users create outlines for adaptable clothing, such as pants that can be reconfigured into a dress. Each component of these pieces can be replaced, rearranged, or restyled.
Read MoreMethod teaches generative AI models to locate personalized objects
After being trained with this technique, vision-language models can better identify a unique item in a new scene.
Read MoreBlending neuroscience, AI, and music to create mental health innovations
Media Lab PhD student Kimaya Lecamwasam researches how music can shape well-being.
Read MoreMIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI
The MIT–MBZUAI Collaborative Research Program will unite faculty and students from both institutions to advance AI and accelerate its use in pressing scientific and societal challenges.
Read MoreUsing generative AI to diversify virtual training grounds for robots
New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
Read MoreFighting for the health of the planet with AI
Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.
Read MoreNew prediction model could improve the reliability of fusion power plants
The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.
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