Dr. Zhengbo Zou is an Assistant Professor in the Department of Civil Engineering at UBC. Dr. Zou received his Ph.D. in Civil Engineering from New York University (2020), his master’s degree in advanced Infrastructure Systems (2015) from Carnegie Mellon University, and his bachelor’s degree in Civil Engineering (2014) from Tongji University. His current research focuses on advancing the knowledge of automation and intelligence in the life cycle of design, construction and maintenance of civil infrastructures.

Research Interests

Building Automation, Facility Management, Responsive Environments, Automation in Construction, Construction Robotics, Virtual/Augmented Reality, Computer Vision, Reinforcement Learning, Stochastic Process.


CIVL 498A Machine Learning in Construction Management
CIVL 520 Construction Planning and Control

Awards & Recognitions

  • 2021, Outstanding Dissertation Award, New York University
  • 2018, Inaugural Class of Urban Doctoral Fellowship, New York University


  • Z. Zou, Yu, X., and Ergan, S., “Towards optimal control of air handling units using deep reinforcement learning and recurrent neural network”, Building and Environment, vol. 168, p. 106535, 2020.
  • S. Ergan, Radwan, A., Zou, Z., Tseng, H. -an, and Han, X., “Quantifying Human Experience in Architectural Spaces with Integrated Virtual Reality and Body Sensor Networks”, Journal of Computing in Civil Engineering, vol. 33, no. 2, p. 04018062, 2019.
  • Z. Zou, Arruda, L., and Ergan, S., “Characteristics of Models that Impact Transformation of BIMs to Virtual Environments to Support Facility Management Operations”, Journal of Civil Engineering and Management, vol. 2419168, no. 66, pp. 481 – 498, 2018.
  • J. Du, Shi, Y., Zou, Z., and Zhao, D., “CoVR: Cloud-Based Multiuser Virtual Reality Headset System for Project Communication of Remote Users”, Journal of Construction Engineering and Management, vol. 144, no. 2, 2018.
  • J. Du, Zou, Z., Shi, Y., and Zhao, D., “Zero latency: Real-time synchronization of BIM data in virtual reality for collaborative decision-making”, Automation in Construction, vol. 85, pp. 51 – 64, 2018.

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