Projects per year
Personal profile
Research Interests
- 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
Personal profile
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.
Teaching
- Architectural Engineering Design 1 (ABEE1025)
- Research Project (ABEE3023)
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Projects
- 1 Active
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Application and Implementation of AI Algorithm in HVAC
15/10/20 → 14/10/23
Project: Contract Projects › Horizontal-Contract Projects out of Zhejiang Province
Research output
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A data-driven clustering analysis for the impact of covid-19 on the electricity consumption pattern of zhejiang province, china
Zhang, Z., Cheshmehzangi, A. & Ardakani, S. P., 1 Dec 2021, In: Energies. 14, 23, 8187.Research output: Journal Publication › Article › peer-review
Open Access1 Citation (Scopus) -
Comprehensive evaluation of energy and indoor-PM2.5-exposure performance of residential window and roller blind control strategies
Zhong, X., Zhang, Z., Wu, W. & Ridley, I., 15 Sep 2020, In: Energy and Buildings. 223, 110206.Research output: Journal Publication › Article › peer-review
6 Citations (Scopus) -
Bio-sensing and reinforcement learning approaches for occupant-centric control
Zhang, C., Zhang, Z. & Loftness, V., 2019, ASHRAE Transactions - 2019 ASHRAE Annual Conference. ASHRAE, p. 364-371 8 p. (ASHRAE Transactions; vol. 125).Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review
1 Citation (Scopus) -
Whole building energy model for HVAC optimal control: A practical framework based on deep reinforcement learning
Zhang, Z., Chong, A., Pan, Y., Zhang, C. & Lam, K. P., 15 Sep 2019, In: Energy and Buildings. 199, p. 472-490 19 p.Research output: Journal Publication › Article › peer-review
83 Citations (Scopus) -
A deep reinforcement learning approach to using whole building energy model for HVAC optimal control
Zhang, Z., Chong, A., Pan, Y., Zhang, C., Lu, S. & Lam, K. P., 2018, In: ASHRAE and IBPSA-USA Building Simulation Conference. p. 675-682 8 p.Research output: Journal Publication › Conference article › peer-review
36 Citations (Scopus)