Dr. Chao Ding is a postdoctoral researcher at Lawrence Berkeley National Laboratory in the Energy Analysis & Environmental Impacts Division. His research interests include natural ventilation, building performance modeling, machine learning, and HVAC system. Dr. Ding’s recent research focuses on urban microclimate modeling and machine learning surrogate model development; high-efficiency low-GWP air conditioner testing and design simulation; urban infrastructure auto-generation based on machine learning and image processing; urban-scale building energy simulation; statistical analysis and validation for the Building Efficiency Targeting Tool for Energy Retrofits (BETTER); smart emerging technology assessment 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.