School of Engineering
School of Engineering

School of Engineering

Artificial Intelligence Computer science and technology DMSE Electrical engineering and computer science (EECS) Electronics Energy machine learning Materials science and engineering Microsystems Technology Laboratories MIT Schwarzman College of Computing MIT.nano Nanoscience and nanotechnology Nuclear science and engineering Research School of Engineering

Nanoscale transistors could enable more efficient electronics

Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.

Artificial Intelligence Awards, honors and fellowships Biology Brain and cognitive sciences Chemical engineering chemistry Computer Science and Artificial Intelligence Laboratory (CSAIL) DMSE Funding Graduate, postdoctoral MIT Schwarzman College of Computing Music Physics School of Engineering School of Humanities Arts and Social Sciences School of Science

MIT Schwarzman College of Computing launches postdoctoral program to advance AI across disciplines

The new Tayebati Postdoctoral Fellowship Program will support leading postdocs to bring cutting-edge AI to bear on research in scientific discovery or music.

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 Research Robotics School of Engineering

A faster, better way to train general-purpose robots

Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Quest for Intelligence Research School of Engineering

Making it easier to verify an AI model’s responses

By allowing users to clearly see data referenced by a large language model, this tool speeds manual validation to help users spot AI errors.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering Video

Combining next-token prediction and video diffusion in computer vision and robotics

A new method can train a neural network to sort corrupted data while anticipating next steps. It can make flexible plans for robots, generate high-quality video, and help AI agents navigate digital environments.

3-D printing Aeronautical and astronautical engineering Aircraft Artificial Intelligence Department of Defense (DoD) Funding machine learning Manufacturing Mechanical engineering Research School of Engineering

Artificial intelligence meets “blisk” in new DARPA-funded collaboration

Collaborative multi-university team will pursue new AI-enhanced design tools and high-throughput testing methods for next-generation turbomachinery.

Algorithms Artificial Intelligence Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Faculty machine learning MIT Schwarzman College of Computing Profile School of Engineering Social networks

Modeling relationships to solve complex problems efficiently

Associate Professor Julian Shun develops high-performance algorithms and frameworks for large-scale graph processing.

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 Research Robotics School of Engineering

How AI is improving simulations with smarter sampling techniques

MIT CSAIL researchers created an AI-powered method for low-discrepancy sampling, which uniformly distributes data points to boost simulation accuracy.

Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) Evolution Imaging Lincoln Laboratory machine learning MIT Schwarzman College of Computing Psychology Research School of Engineering School of Science

AI pareidolia: Can machines spot faces in inanimate objects?

New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Autonomous vehicles computer-vision Disaster response Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory machine learning MIT Schwarzman College of Computing Natural disasters Research Robotics School of Engineering

Helping robots zero in on the objects that matter

A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.