Haifeng Lan is a Ph.D. researcher at the Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, where he focuses on intelligent built environment systems and thermal comfort modeling. His research spans data‑driven approaches to indoor environmental quality, including computer vision and machine learning‑based strategies for optimizing indoor thermal comfort and HVAC performance. Haifeng has contributed to multiple peer‑reviewed publications on smart HVAC control and occupant‑centric thermal comfort prediction in university classrooms and building environments. Prior to his doctoral studies, he gained research experience in environmental design and sustainable building technologies. His work integrates interdisciplinary methods from machine learning, building physics, and human‑environment interaction to advance energy‑efficient indoor climate solutions.
Haifeng Lan is a Ph.D. researcher at the Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, where he focuses on intelligent built environment systems and thermal comfort modeling. His research spans data‑driven approaches to indoor environmental quality, including computer vision and machine learning‑based strategies for optimizing indoor thermal comfort and HVAC performance. Haifeng has contributed to multiple peer‑reviewed publications on smart HVAC control and occupant‑centric thermal comfort prediction in university classrooms and building environments. Prior to his doctoral studies, he gained research experience in environmental design and sustainable building technologies. His work integrates interdisciplinary methods from machine learning, building physics, and human‑environment interaction to advance energy‑efficient indoor climate solutions.