Research
Research

Research

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

MIT researchers develop an efficient way to train more reliable AI agents

The technique could make AI systems better at complex tasks that involve variability.

Algorithms Artificial Intelligence Climate change Computer modeling Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Environment MIT Schwarzman College of Computing Plants Research School of Engineering Sustainability Urban studies and planning

Advancing urban tree monitoring with AI-powered digital twins

The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.

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

Can robots learn from machine dreams?

MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI’s potential for creating robotics training data.

Artificial Intelligence Arts Civil and environmental engineering Computer science and technology Design machine learning Materials science and engineering Mechanical engineering Research School of Engineering

Graph-based AI model maps the future of innovation

An AI method developed by Professor Markus Buehler finds hidden links between science and art to suggest novel materials.

Algorithms Artificial Intelligence Computer science and technology Data Design Human-computer interaction Interview machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

3 Questions: Inverting the problem of design

MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.

Algorithms Artificial Intelligence Biological engineering Broad Institute Cells Computer science and technology Data Electrical engineering and computer science (EECS) Genetic engineering Genetics IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

A causal theory for studying the cause-and-effect relationships of genes

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.

3-D printing Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) Human-computer interaction Light machine learning Maker movement Mechanical engineering Media Lab MIT Schwarzman College of Computing Research School of Engineering School of Science Wearable sensors Wearables

A portable light system that can digitize everyday objects

A new design tool uses UV and RGB lights to change the color and textures of everyday objects. The system could enable surfaces to display dynamic patterns, such as health data and fashion designs.

Algorithms Artificial Intelligence Computer science and technology Economics Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering School of Humanities Arts and Social Sciences

Despite its impressive output, generative AI doesn’t have a coherent understanding of the world

Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.

Algorithms Artificial Intelligence Data Electrical engineering and computer science (EECS) Equity and inclusion Ethics IDSS machine learning MIT Schwarzman College of Computing MIT Sloan School of Management Open access Policy Racism Research School of Engineering Social justice Social sciences Technology and policy

Empowering systemic racism research at MIT and beyond

Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.

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.