MIT Schwarzman College of Computing

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MIT welcomes David Siegel SM ’86, PhD ’91 as its next Innovation Fellow

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David Siegel SM ’86, PhD ’91, a computer scientist, entrepreneur, and philanthropist, will serve as the next MIT Innovation Fellow during the 2026-27 academic year. Working with the MIT Schwarzman College of Computing, Siegel will explore how artificial intelligence can accelerate scientific discovery at the Institute and beyond.“From the MIT Schwarzman College of Computing to […]

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

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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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Measure by measure, studying society accurately

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Let’s agree at the outset the world is a complicated place, and social scientists have exacting jobs when it comes to measuring civic phenomena with precision. After all, even careful studies raise follow-up questions: How much do their findings apply in other settings? Do conclusions about politics in one country apply to other countries? If you’re

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New method enables AI for safety-critical situations

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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

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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

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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

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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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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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How an MIT research project became a global programming language

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It all started with some exasperated emails. Back in 2009, a group of researchers began venting their frustration with the programming languages designed to help scientists and other researchers perform complex mathematical operations and statistical simulations without learning how to code. These programming languages were rigid and slow. If scientists built something that really worked,

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Generating scenarios for extreme events, without extreme data

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Can a city’s seawall stand up to a blockbuster storm? Will a region’s power grid hold against record-breaking heat? And can a town’s fire-fighting resources contain a major wildfire? To answer these questions, communities will first need to know how such extreme events could unfold. How far is a wildfire likely to spread? How much of

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