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Research activity per year

Personal profile

Research Interests

  • Data-driven and physics-based modeling and calibration of integrated energy systems
  • Energy efficient control and operation of industrial HVAC systems
  • Smart and low carbon buildings, communities and industrial parks

Personal profile

Dr. Zhang has international and interdisciplinary experience in both building and urban energy systems 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 integrated energy systems at community and urban scale. His research covers various aspects of artificial intelligence, including deep learning, reinforcement learning, Bayesian methods, etc. The models and algorithm he developed has been implemented and validated in real-life commercial projects.


  • Architectural Engineering Design 1 (ABEE1025)
  • Research Project (ABEE3023)
  • Smart Energy Systems

Education/Academic qualification

PhD, Building Performance and Diagnostics, Carnegie Mellon University

Aug 2016Dec 2019

Award Date: 18 Dec 2019

Master, Building Performance and Dianostics, Carnegie Mellon University

Aug 2014May 2016

Award Date: 15 May 2016

Bachelor, Architectural Environment Engineering

Sept 2010Jul 2014

Award Date: 7 Jul 2014

Person Types

  • Staff


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