Algorithms
Algorithms

Algorithms

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Graduate, postdoctoral Interview machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Pollution Research School of Engineering Students Sustainability

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.

Algorithms Alternative energy Artificial Intelligence Computer science and technology Electrical engineering and computer science (EECS) Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

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.

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Creating AI that matters

How the MIT-IBM Watson AI Lab is shaping AI-sociotechnical systems for the future.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering Video

Method 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.

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Optimizing food subsidies: Applying digital platforms to maximize nutrition

An algorithm can change the face of food assistance policy in the Global South, says MIT assistant professor and J-WAFS researcher Ali Aouad.

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Helping scientists run complex data analyses without writing code

Co-founded by an MIT alumnus, Watershed Bio offers researchers who aren’t software engineers a way to run large-scale analyses to accelerate biology.

Algorithms Artificial Intelligence Climate change Computer science and technology Electric grid Electrical engineering and computer science (EECS) Energy Faculty Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Profile Renewable energy School of Engineering Sustainability Technology and policy

Fighting for the health of the planet with AI

Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.

Algorithms Antibiotics Artificial Intelligence Bacteria Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Disease Drug development Drug discovery Electrical engineering and computer science (EECS) Health Care Health sciences and technology Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing Research School of Engineering Viruses

AI maps how a new antibiotic targets gut bacteria

MIT CSAIL and McMaster researchers used a generative AI model to reveal how a narrow-spectrum antibiotic attacks disease-causing bacteria, speeding up a process that normally takes years.

Algorithms Artificial Intelligence Climate change Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Emissions Energy Energy storage Infrastructure Lincoln Laboratory machine learning MIT Energy Initiative MIT Schwarzman College of Computing MIT Sloan School of Management Research School of Engineering Supercomputing Sustainable computing

Responding to the climate impact of generative AI

Explosive growth of AI data centers is expected to increase greenhouse gas emissions. Researchers are now seeking solutions to reduce these environmental harms.

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MIT affiliates win AI for Math grants to accelerate mathematical discovery

Department of Mathematics researchers David Roe and Andrew Sutherland seek to advance automated theorem proving; four additional MIT alumni also awarded.