• Learning-based adaptive control for building energy systems
• Building energy model-based control and operation
• Digital-twin for HVAC systems via BIM/BEM fusion
• Occupant-oriented building for human comfort and wellbeing

Dr. Zhang has international and interdisciplinary experience in both building technologies and data science. He obtained his Bachelor's degree in the field of building services engineering at the University of Nottingham. After that, he completed his Ph.D. with a focus on reinforcement learning-based HVAC control from Carnegie Mellon University in 2019. During his Ph.D., he was also a visiting researcher at the National University of Singapore, where he conducted research on Bayesian calibration of building energy models. Before joining UNNC in 2020, Dr. Zhang worked as a senior algorithm engineer in Alibaba Cloud. In Alibaba, he was responsible for the development of the data intelligence algorithms for city-level energy systems, including district heating/cooling systems and water systems.

Currently, Dr. Zhang’s research focuses on the fusion of artificial intelligence and building energy systems. His research covers various aspects of artificial intelligence, including deep learning, reinforcement learning, evolutionary algorithm, Bayesian methods, etc. In addition, he is also specialized in green/healthy building certifications, such as LEED, BREEAM, and WELL.

• Architectural Engineering Design 1 (ABEE1025)
• Research Project (ABEE3023)