A new way to integrate data with physical objects
StructCode, developed by MIT CSAIL researchers, encodes machine-readable data in laser-cut objects by modifying their fabrication features.
StructCode, developed by MIT CSAIL researchers, encodes machine-readable data in laser-cut objects by modifying their fabrication features.
Center for Ultracold Atoms gets funding boost to “punch through tough scientific barriers and see what's on the other side.”
Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.
Five MIT faculty, along with seven additional affiliates, are honored for outstanding contributions to medical research.
MIT engineers develop a long, curved touch sensor that could enable a robot to grasp and manipulate objects in multiple ways.
Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.
MIT Digital Learning Lab advances quality digital learning on campus and globally.
Open-source software by MIT MAD Fellow Jonathan Zong and others in the MIT Visualization Group reveals online graphics’ embedded data in the user’s preferred degree of granularity.
By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.
Grants fund studies of honeybee tracking, glass building materials, and defining excellence in human movement.
With the growing use of AI in many disciplines, the popularity of MIT’s four “blended” majors has intensified.
By analyzing epigenomic and gene expression changes that occur in Alzheimer’s disease, researchers identify cellular pathways that could become new drug targets.
Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.
The program supports “outstanding theoretical scientists.”
Co-directors Youssef Marzouk and Nicolas Hadjiconstantinou describe how the standalone degree aims to train students in cross-cutting aspects of computational science and engineering.