Timeless virtues, new technologies
Engineer and historian David Mindell’s new book provides a roadmap for thinking about the future of industry.
Engineer and historian David Mindell’s new book provides a roadmap for thinking about the future of industry.
Doug Field SM ’92, Ford’s chief of EVs and digital design, leads the legacy carmaker into the software-enabled, battery-propelled future.
The consortium will bring researchers and industry together to focus on impact.
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
With seven new startups, MIT.nano's program for hard-tech ventures expands to more than 20 companies.
The neuroscientist turned entrepreneur will be hosted by the MIT Schwarzman College of Computing and focus on advancing the intersection of behavioral science and AI across MIT.
The company has announced that it will build the first grid-scale fusion power plant in Chesterfield County, Virginia.
The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advanced vehicle technology.
The startup Alsym Energy, co-founded by Professor Kripa Varanasi, is hoping its batteries can link renewables with the industrial sector and beyond.
The MIT Energy Initiative and a consortium of Taiwanese companies are exploring how Taiwan can secure its energy future as the world transitions away from fossil fuels.
The 16th Annual Meeting of the Kendall Square Association honored community members for their work bringing impactful innovations to bear on humanity’s biggest challenges.
Professor Ellen Roche is creating the next generation of medical devices to help repair hearts, lungs, and other tissues.
Context Labs, led by Dan Harple SM ’13, uses AI-enabled data analytics and verification to help companies measure their true greenhouse emissions and document reductions.
Two studies pinpoint their likely industrial sources and mitigation opportunities.
In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.