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Optimizing nuclear fuels for next-generation reactors
While working to nurture scientific talent in his native Nigeria, Assistant Professor Jossou is setting his sights on using materials science and computation to design robust nuclear components.
New algorithm unlocks high-resolution insights for computer vision
FeatUp, developed by MIT CSAIL researchers, boosts the resolution of any deep network or visual foundation for computer vision systems.
Researchers help robots navigate efficiently in uncertain environments
A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination.
Researchers enhance peripheral vision in AI models
By enabling models to see the world more like humans do, the work could help improve driver safety and shed light on human behavior.
Method rapidly verifies that a robot will avoid collisions
Faster and more accurate than some alternatives, this approach could be useful for robots that interact with humans or work in tight spaces.
Dealing with the limitations of our noisy world
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
Eight from MIT named 2024 Sloan Research Fellows
Fellows honored for creativity, innovation, and research accomplishments.
New AI model could streamline operations in a robotic warehouse
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
Generative AI for smart grid modeling
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.
Automated method helps researchers quantify uncertainty in their predictions
An easy-to-use technique could assist everyone from economists to sports analysts.
