Gnu-RL: A precocial reinforcement learning solution for building HVAC control using a Differentiable MPC policy
Best Paper Award at ACM BuildSys'20
Type
Publication
Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation
Bingqing Chen
Machine Learning Research Scientist
My primary research interest is in making reinforcement learning agents safe and sample-efficient to be viable for real-world applications. I work on autonomous energy systems to 1) improve energy efficiency, and 2) facilitate renewable energy integration.
Mario Bergés
Professor of Civil and Environmental Engineering
My research interests vary, but generally gravitate towards the development of technologies to make our built enviornment and the communities in them more autonomous and efficient. Lately I am interested in developing responsible autonomous solutions for infrastructure systems.