New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.
New technique could diminish errors that hamper the performance of super-fast analog optical neural networks.
MIT undergraduate researchers Helena Merker, Harry Heiberger, and Linh Nguyen, and PhD student Tongtong Liu, exploit machine-learning techniques to determine the magnetic structure of materials.
Battery power from electric vehicles to the grid could open a fast lane to a net-zero future.
Researchers have developed a programmable optical device for high-speed beam steering.
Recent mechanical engineering alumna Emily Satterfield ’22 pursues passions that might seem unrelated but “actually go hand-in-hand.”
VulcanForms, founded by an MIT alumnus and professor, has created digital production systems to manufacture complex metal parts at scale.
The MIT senior will pursue postgraduate studies in computer science in Ireland.
New research reveals a scalable technique that uses synthetic data to improve the accuracy of AI models that recognize images.
New system can teach a group of cooperative or competitive AI agents to find an optimal long-term solution.
Associate Professor Otto Cordero is looking for the fundamental constraints that shape microbial ecosystems.
Researchers harness new pooled, image-based screening method to probe the functions of over 5,000 essential genes in human cells.
New prize program recognizes MIT researchers who make data openly accessible and reusable.
A new technique that accurately measures how atom-thin materials expand when heated could help engineers develop faster, more powerful electronic devices.
For some MIT Leaders for Global Operations graduates, a research passion becomes a full-time career.