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MIT affiliates win 2026 Hertz Foundation Fellowships

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Awards, honors and fellowships, Chemistry, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Graduate, postdoctoral, Mechanical engineering, MIT Schwarzman College of Computing, Robotics, School of Engineering, School of Science, Students

The Hertz Foundation announced that it awarded 2026 fellowships to three current MIT students as well as an incoming graduate student. They are: Annika Marschner, Alvin Q. Meng, Zachary S. Siegel, and Matthew Wanta.The prestigious science and technology award provides each recipient with five years of financial support — a stipend and full tuition equivalent — which gives them […]

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Startup’s nuclear-inspired cooling system could make data centers more sustainable

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, Energy, Energy efficiency, Energy storage, Innovation and Entrepreneurship (I&E), Nuclear science and engineering, School of Engineering, Startups, Sustainability, Sustainable computing, Technology and society, Water

The rise of artificial intelligence is riding on the back of an enormous data center expansion. Data centers are projected to account for anywhere from 9 to 17 percent of total electricity usage in the U.S. by the end of the decade. Today, around a third of data center electricity is devoted to cooling the

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The crucial human component in computing and AI

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Artificial Intelligence, Comparative Media Studies/Writing, Education, teaching, academics, Electrical engineering and computer science (EECS), ethics, Human-computer interaction, IDSS, Media Lab, MIT Schwarzman College of Computing, MIT Sloan School of Management, Music and theater arts, Philosophy, Political science, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Special events and guest speakers, Technology and society

On April 30, the MIT Schwarzman College of Computing’s Social and Ethical Responsibilities of Computing (SERC) initiative hosted a full-day research symposium examining how artificial intelligence is shaping the world and its implications for society. The symposium included research talks by SERC’s latest seed grant recipients on topics such as air pollution forecasting and responsible computer vision deployment, panels on AI alignment

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NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Astronomy and astrophysics, Chemistry, Collaboration, Computer science and technology, data, DMSE, Funding, IDSS, Machine Learning, Mathematics, MIT Schwarzman College of Computing, National Science Foundation (NSF), Physics, Research, School of Engineering, School of Science

The MIT-led Institute for Artificial Intelligence and Fundamental Interactions (IAIFI) has received renewed support from the National Science Foundation (NSF) for an additional five years, increasing annual funding from $4 million to $4.98 million. The renewal marks a new phase for IAIFI, which has spent its first five years building a research model and an

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Teaching AI agents to ask better questions by playing “Battleship”

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Games, Machine Learning, MIT Schwarzman College of Computing, MIT Siegel Family Quest for Intelligence, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Natural Language Processing, Programming, Research, School of Engineering, School of Science

In 2026, the hype for artificial intelligence agents is louder than ever before. These semi-autonomous programs can “think” and execute well-defined tasks in areas like customer service and software development, typically using language models (LMs). But fields like medical diagnosis and scientific discovery require them to inquire about a vast range of solutions in uncertain

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MIT researchers teach AI models to interpret charts

ai, AI (Artificial Intelligence), Artificial Intelligence, Business and management, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, data, Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Computing Research Lab, Research, School of Engineering

To accelerate and refine decision-making in a fast-paced, global marketplace, enterprises may deploy generative artificial intelligence models to help summarize and interpret the charts that often fill market summaries and financial reports.But even the latest vision-language models sometimes struggle with this task, since it requires a model to integrate visual, numerical, and linguistic understanding. A

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Building AI models that understand chemical principles

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Chemical engineering, Chemistry, Computer science and technology, Drug discovery, Electrical engineering and computer science (EECS), Faculty, Machine Learning, MIT Schwarzman College of Computing, Profile, School of Engineering

Among all of the possible chemical compounds, it’s estimated that between 1020 and 1060 may hold potential as small-molecule drugs.Evaluating each of those compounds experimentally would be far too time-consuming for chemists. So, in recent years, researchers have begun using artificial intelligence to help identify compounds that could make good drug candidates. One of those researchers is MIT

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Justin Solomon appointed associate dean of engineering education

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Education, teaching, academics, Electrical engineering and computer science (EECS), Faculty, Institute for Medical Engineering and Science (IMES), Leadership, Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, School of Engineering

Justin Solomon, associate professor in the MIT Department of Electrical Engineering and Computer Science (EECS), has been appointed associate dean of engineering education in the MIT School of Engineering, effective July 1.In this new role, Solomon will focus on advancing innovation in engineering education across the school. He will help shape new pedagogical approaches in

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Two from MIT named 2026 Knight-Hennessy Scholars

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, Awards, honors and fellowships, Economics, Electrical engineering and computer science (EECS), Graduate, postdoctoral, Mathematics, Physics, Robotics, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Students

MIT master’s student Sunshine Jiang ’25 and Rupert Li ’24 are recipients of this year’s Knight-Hennessy Scholarship. Now in its ninth year, the highly competitive scholarship provides up to three years of financial support for graduate studies at Stanford University. Sunshine Jiang  ’25Sunshine Jiang, from Hangzhou, China, graduated from MIT in 2025 with a bachelor’s degree

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Games people — and machines — play: Untangling strategic reasoning to advance AI

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), Faculty, Game theory, Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Profile, School of Engineering

Gabriele Farina grew up in a small town in a hilly winemaking region of northern Italy. Neither of his parents had college degrees, and although both were convinced they “didn’t understand math,” Farina says, they bought him the technical books he wanted and didn’t discourage him from attending the science-oriented, rather than the classical, high

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