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.
Faster and more accurate than some alternatives, this approach could be useful for robots that interact with humans or work in tight spaces.
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
Fellows honored for creativity, innovation, and research accomplishments.
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
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.
The printed solenoids could enable electronics that cost less and are easier to manufacture — on Earth or in space.
An MIT team precisely controlled an ultrathin magnet at room temperature, which could enable faster, more efficient processors and computer memories.
Undergraduates selected for the competitive program enjoy a seminar series and conversations over dinners with distinguished faculty.
An easy-to-use technique could assist everyone from economists to sports analysts.
Adaptive smart glove from MIT CSAIL researchers can send tactile feedback to teach users new skills, guide robots with more precise manipulation, and help train surgeons and pilots.
MIT engineers developed a tag that can reveal with near-perfect accuracy whether an item is real or fake. The key is in the glue on the back of the tag.
Innovative AI system from MIT CSAIL melds simulations and physical testing to forge materials with newfound durability and flexibility for diverse engineering uses.
Researchers developed a simple yet effective solution for a puzzling problem that can worsen the performance of large language models such as ChatGPT.
Scientists quantify a previously overlooked driver of human-related mercury emissions.