Han Li

Han Li is a Senior Scientific Engineering Associate at Lawrence Berkeley National Laboratory. He specializes in using interdisciplinary knowledge and techniques – including building physics, AI, machine learning and software engineering – to develop innovative solutions for enhancing building energy efficiency, demand flexibility and semantic data interoperability across different scopes. He has been a lead performer for various DOE-funded projects and a contributor to international collaborations including IEA EBC Annex 79, Annex 81 and IEEE FlexGEB. He leads the technical development of the DOE BETTER tool and contributes to CityBES, which won the 2020 and 2022 R&D100 awards, respectively. He is currently pursuing a PhD in Building Performance and Diagnostics focusing on data-driven modeling and optimal building controls for demand flexibility and resilience.

Research Interests

• Building physics
• AI 
• Demand flexibility 
• Semantic interoperability

Affiliation

• Lawrence Berkeley National Laboratory