Chao Ding is a project scientist in the International Energy Analysis Department at Lawrence Berkeley National Lab. His research interests are cooling efficiency, Heating, Ventilation, Air conditioning and Refrigeration (HVAC&R) system, natural ventilation, building performance modeling, and machine learning. His current research projects include High-efficiency low-GWP air conditioner development; Equipment energy efficiency improvement; Computational fluid dynamics (CFD) modeling; Statistical analysis and validation for the Building Efficiency Targeting Tool for Energy Retrofits (BETTER); Machine learning for urban infrastructure generation etc.
He holds a Ph.D. in Building Performance and Diagnostics from Carnegie Mellon University, an M.S. in Mechanical Engineering from Carnegie Mellon University and an M.S. in HVAC from Tongji University, China.