Haiyan Hao is an assistant professor who joined the School of Humanities and Social Science at CUHK(Shenzhen) in 2023 Fall. Her research focused on leveraging advanced analytics and computing approaches to empower human communities in tackling the varied social and environmental challenges, such as technology disruptions and extreme events. Before she joined HSS at CUHK(SZ), she has worked on several NSF-funded projects related to smart and resilient communities. The research outcomes were published on several top-tier journals.


Research Interest:

- applying AI techniques to support urban scenario planning and participatory planning.

- developing digital twin as a tool supporting public service, urban management, and urban planning.

- conducting data analyses to understand complex urban dynamics and phenomenon.

- exploring unequal technology innovations across social groups and geography, and developing strategies to mitigating the negative impacts.

Awards and honors
  • 2023
  • 2022
  • 2021
  • 2019
  • 01


    Paul and Malea Zwick Graduate Student Award awarded by department of Urban and Regional Planning at University of Florida ($1,000)

  • 02


    Certificate of Outstanding Merit awarded by International Center of University of Florida

  • 03


    Research Promotion Initiative awarded by University Florida’s Office of Strategic Communications and Marketing ($2,000).

  • 04


    Graduate School Funding Award awarded by Graduate School of University of Florida ($34,000/year for four years)


(*: corresponding author)

Journal Publication

  • Hao, H., & Wang, Y.* (2023). Modeling Dynamics of Community Resilience to Extreme Events with Explainable Deep Learning. Natural Hazards Review, 24(2), 04023013. 

  • Hao, H., Wang, Y.*, Du, L., & Chen, S. (2023). Enabling smart curb management with spatiotemporal deep learning. Computers, Environment and Urban Systems, 99, 101914.

  • Hao, H., & Wang, Y.* (2022). Disentangling relations between urban form and urban accessibility for resilience to extreme weather and climate events. Landscape and Urban Planning, 220, 104352.

  • Hao, H., Wang, Y.*, & Kang, S. (2022). Examining “digital” vulnerability to flooding among subsidized housing residents in Florida. International Journal of Disaster Risk Reduction, 82, 103302.

  • Hao, H., & Wang, Y*. (2021). Assessing Disaster Impact in Real Time: Data-Driven System Integrating Humans, Hazards, and the Built Environment.  Journal of Computing in Civil Engineering,  35(5), 04021010.

  • Hao, H., & Wang, Y*. (2020). Leveraging multimodal social media data for rapid disaster damage assessment.  International Journal of Disaster Risk Reduction, 51, 101760.

  • Wang, Y.*, Hao, H., & Platt, L. S. (2021). Examining risk and crisis communications of government agencies and stakeholders during early-stages of COVID-19 on Twitter.  Computers in human behavior,  114, 106568.

  • Wang, Y.*, Hao, H.,  Wang, C. (2022). Preparing Urban Curbside for Increasing Mobility-on-Demand using Data-Driven Agent-Based Simulation: Case Study of City of Gainesville, Florida.  Journal of Management in Engineering.

  • Hao, H., Li, Y.*, Medina, A., Gibbons, R.B., & Wang, L. (2020). Understanding crashes involving roadway objects with SHRP 2 naturalistic driving study data.  Journal of safety research,  73, 199-209. 

  • Li, Y.*, Hao, H., Gibbons, R.B., & Medina, A. (2021). Understanding Gap Acceptance Behavior at Unsignalized Intersections using Naturalistic Driving Study Data.  Transportation Research Record,  2675(9) 1345–1358. 

  • Li, Y.*, Hao, H., Gibbons, R.B., & Medina, A. (2020). Implications of crashes involving roadway objects for machine vision-based driving systems.  Transportation research record,  2674(12), 291-302. 

Conference Publication

  • Hao, H., & Wang, Y*. (2022) Smart Curb Digital Twin: Inventorying Curb Environments using Computer Vision and Street Imagery. 2nd Annual International Conference on Digital Twins and Parallel Intelligence (IEEE DTPI 2022). Boston, U.S. 

    Hao, H., Wang, Y.*, & Wang, Q. (2022) Simulating Urban Population Activities under Extreme Events with Data-Driven Agent-Based Modeling. 2022 ASCE’s Construction Institute and Construction Research Council. Arlington, VA; March 9-12, 2022. 

    Hao, H., Wang, Y.*. (2020). Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami. In 17th International Conference on Information Systems for Crisis Response and Management (pp. 825–837). Blacksburg, VA (USA): Virginia Tech.