How artificial intelligence can help achieve a clean energy future
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more.
The virtual VideoCAD tool could boost designers’ productivity and help train engineers learning computer-aided design.
Industry leaders agree collaboration is key to advancing critical technologies.
Professors Facundo Batista and Dina Katabi, along with three additional MIT alumni, are honored for their outstanding professional achievement and commitment to service.
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.
Incorporating machine learning, MIT engineers developed a way to 3D print alloys that are much stronger than conventionally manufactured versions.
The research center, sponsored by the DoE’s National Nuclear Security Administration, will advance the simulation of extreme environments, such as those in hypersonic flight and atmospheric reentry.
Popular mechanical engineering course applies machine learning and AI theory to real-world engineering design.
MIT engineers used a machine-learning model to design nanoparticles that can deliver RNA to cells more efficiently.
The Initiative for New Manufacturing is convening experts across the Institute to drive a transformation of production across the U.S. and the world.