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New AI technique could make minimally invasive surgeries safer and more precise

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical engineering and computer science (EECS), Health care, Imaging, Jameel Clinic, Machine Learning, Medical devices, MIT Schwarzman College of Computing, MIT-IBM Computing Research Lab, National Institutes of Health (NIH), Research, School of Engineering

Researchers created a new technique that accurately and rapidly matches X-rays captured during surgery with a patient’s preoperative 3D medical scan. This method could make it easier for clinicians to precisely pilot minimally invasive surgical tools, leading to faster and safer procedures.Clinicians perform many minimally invasive surgeries using real-time X-rays to help them steer devices […]

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MIT spinout turns plastic waste into resilient building materials

3-D printing, ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Cleaner industry, Housing, Innovation and Entrepreneurship (I&E), Materials science and engineering, Mechanical engineering, Pollution, Robotics, School of Engineering, Startups, Sustainability

The world needs more homes. The world also has too much plastic. Perhaps the only thing those two problems have in common is that they’re hard to solve.Atlas Building Composites, a spinout of MIT, is on a mission to address both problems with a single solution. The company has developed an AI-powered robotic manufacturing platform

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New method enables AI for safety-critical situations

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, Research, Robotics, School of Engineering

MIT researchers have developed a new technique that helps generative artificial intelligence models find solutions to high-stakes problems.In these settings, a plausible answer is not enough: The output often must also satisfy nonnegotiable safety, physical, or task-specific requirements, known as hard constraints.The researchers developed a method that helps generative models meet these strict requirements without

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MIT Schwarzman College of Computing launches pilot to help educators teach AI across disciplines

ai, AI (Artificial Intelligence), Artificial Intelligence, Civil and environmental engineering, Classes and programs, Computer science and technology, Education, teaching, academics, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT Sloan School of Management, School of Engineering, Special events and guest speakers, STEM education

This summer, the MIT Schwarzman College of Computing welcomed faculty from colleges and universities across Greater Boston, South Carolina, West Virginia, and Texas to campus for the inaugural AI Educators Pilot, a weeklong workshop aimed at expanding how artificial intelligence is taught across disciplines and learning environments. Inspired by MIT class C01/C51 (Modeling with Machine Learning),

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From MIT to IBM, expediting AI and quantum deployment

ai, AI (Artificial Intelligence), Algorithms, Alumni/ae, Artificial Intelligence, Careers, Collaboration, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), Graduate, postdoctoral, Industry, Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Computing Research Lab, MIT-IBM Watson AI Lab, Quantum Computing, School of Engineering

The experience of transitioning from research based in theory to focusing on real-world application can vary significantly for different researchers. However, for two former MIT graduate students and a former postdoc, all now at IBM, working with the MIT-IBM Computing Research Lab (formerly the MIT-IBM Watson AI Lab) during their formative years enabled them to

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System helps humans predict when self-driving cars will make mistakes

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Artificial Intelligence, Autonomous vehicles, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Research, Robotics, School of Engineering

Self-driving cars are often controlled by deep learning models that sometimes fail in unexpected situations. For instance, the car might inexplicably brake and block the path of an oncoming emergency vehicle. A human driver or passenger may need to react rapidly to prevent a collision.To help humans better anticipate a vehicle’s mistakes, researchers from MIT

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Walter Torous named executive director of MIT Center for Real Estate

ai, AI (Artificial Intelligence), Architecture, Artificial Intelligence, Center for Real Estate, Civil and environmental engineering, Education, teaching, academics, Leadership, Machine Learning, Media Lab, MIT Sloan School of Management, Real Estate, School of Architecture and Planning, School of Engineering, Urban studies and planning

Walter Torous, senior lecturer in the MIT Department of Urban Studies and Planning (DUSP) and the MIT Sloan School of Management, and director of the Master of Science in Real Estate Development Program (MSRED), was recently named executive director of the MIT Center for Real Estate (CRE) — effective July 1, 2026.In announcing Torous’ appointment, School of Architecture

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MIT Quantum Initiative launches postdoctoral fellowship program

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The MIT Quantum Initiative (QMIT) has launched a new postdoctoral fellowship program to accelerate interdisciplinary quantum research and develop the next generation of scientific leaders working at the frontiers of quantum science and technology.Supported by a grant from the Gordon and Betty Moore Foundation, the program reflects QMIT’s vision of expanding the boundaries of quantum science

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Looking beyond natural sequences

ai, AI (Artificial Intelligence), Artificial Intelligence, Biological engineering, Biology, Computer science and technology, Machine Learning, Proteins, Research, School of Engineering, School of Science

A protein’s function is determined by its structure, and structure — the way a protein folds — is determined by its sequence of amino acids, the building blocks of proteins. Many methods for designing novel proteins, including examples that could bind to a disease-causing molecule in our cells, involve a two-step process: The structure comes first,

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AI helps design new materials that work in the real world

ai, AI (Artificial Intelligence), Artificial Intelligence, Chemical engineering, Chemistry, Computer science and technology, Department of Energy (DoE), DMSE, Machine Learning, Materials science and engineering, National Science Foundation (NSF), Nuclear science and engineering, Physics, Research, School of Engineering, School of Science, semiconductors

Today, anyone with a large enough artificial intelligence model can generate millions of new material designs in minutes. Unfortunately, that hasn’t led to a huge leap in the number of new materials being used to improve the performance of products like computer chips and rockets.One reason for the translation gap is that current models don’t

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