Remembering Professor Emerita Jeanne Shapiro Bamberger, a pioneer in music education
The former department chair was an early innovator in the use of artificial intelligence to both study and influence how children learn music.
Artificial Intelligence
Blending neuroscience, AI, and music to create mental health innovations
Media Lab PhD student Kimaya Lecamwasam researches how music can shape well-being.
Read MoreOptimizing food subsidies: Applying digital platforms to maximize nutrition
An algorithm can change the face of food assistance policy in the Global South, says MIT assistant professor and J-WAFS researcher Ali Aouad.
Read MoreChecking the quality of materials just got easier with a new AI tool
Acting as a “virtual spectrometer,” SpectroGen generates spectroscopic data in any modality, such as X-ray or infrared, to quickly assess a material’s quality.
Read MoreHelping scientists run complex data analyses without writing code
Co-founded by an MIT alumnus, Watershed Bio offers researchers who aren’t software engineers a way to run large-scale analyses to accelerate biology.
Read MoreRay Kurzweil ’70 reinforces his optimism in tech progress
Receiving the Robert A. Muh award, the technologist and author heralded a bright future for AI, breakthroughs in longevity, and more.
Read MoreMIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI
The MIT–MBZUAI Collaborative Research Program will unite faculty and students from both institutions to advance AI and accelerate its use in pressing scientific and societal challenges.
Read MoreUsing generative AI to diversify virtual training grounds for robots
New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.
Read MoreFighting for the health of the planet with AI
Assistant Professor Priya Donti’s research applies machine learning to optimize renewable energy.
Read MoreNew prediction model could improve the reliability of fusion power plants
The approach combines physics and machine learning to avoid damaging disruptions when powering down tokamak fusion machines.
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