New machine learning technique can help
Combining capture and disposal
Analysis points the way to energy-efficient systems
Conserving energy with the ideal ceiling fan
Why including non-carbon options is key
Producing electricity from industrial waste heat
Broad applications for new, low-cost porous materials
Compact, durable motors that don't overheat
Enabling smaller, lighter, faster computers
Does replacing coal with wood lower CO2 emissions?
January 2018
John Sterman
Machine Learning from Schools about Energy Efficiency
September 2017
Christopher Knittel
Toward an Energy Efficient Language and Compiler for (Partially) Reversible Algorithms
June 2016
Erik Demaine, Jayson Lynch
Materials Science and Engineering
Chemical Engineering
Civil and Environmental Engineering
Electrical Engineering & Computer Science
Nuclear Science and Engineering
Mechanical Engineering
Sloan School of Management
MIT Energy Initiative
Office of the Provost
Urban Studies & Planning
Chemistry
MIT Media Lab
Computer Science and Artificial Intelligence
Architecture
Earth, Atmospheric, and Planetary Science
Aeronautics and Astronautics
