Yuebing Liang

Yuebing Liang

Assistant Professor @ THU; Postdoc @ MIT; PhD @ HKU

About Me

I am a Ph.D. supervisor and Tenure-Track Assistant Professor at the Department of Urban Planning, Tsinghua University (THU). Before that, I was a Postdoc Associate at SMART Centre, MIT under the supervision of Prof. Zhao Jinhua. I obtained my Ph.D. degree from The University of Hong Kong (HKU), supervised by Prof. Zhao Zhan. I was also a visiting PhD student at MIT Senseable City Lab, supervised by Prof. Carlo Ratti and Prof. Paolo Santi. I received my bachelor and master degrees from Tsinghua University.

I am always seeking highly motivated students to work with. Interested candidates are strongly encouraged to contact me via email, along with their resume. For those interested in PhD/Master positions in Fall 2028, early contact and potential collaboration experience is strongly encouraged to help us know each other.

My research interest lies in the intersection of Artificial Intelligence, Human Mobility and Urban Planning:

  • Spatiotemporal Intelligence for Human Mobility Modeling: Developing spatiotemporal deep learning algorithms to model and predict human mobility in complex transportation systems. My previous work includes multimodal travel demand prediction, simulating potential demand distributions in newly planned transport networks, and analyzing irregular mobility patterns during special events.
  • Artificial Intelligence for Urban and Transport Planning: Applying advanced AI methods—such as generative AI and deep reinforcement learning—to inform and optimize urban and transport planning decisions. Recent projects include designing transit-oriented development strategies through reinforcement learning and enabling human-in-the-loop urban design through diffusion-based generative models.
  • Big Data and Travel Behavior Analysis: Leveraging large-scale urban data alongside statistical and machine learning techniques to understand individual travel decisions and their relationship with the built environment, enabling data-driven planning and policy evaluation. Recent studies include analyzing post-pandemic travel behavior patterns and exploring activity planning heterogeneity across different social groups.

News

  • [2026-10] [2026-10] Our paper “Long-term dynamics of functional restructuring and spatial upgrading in Gusu District, Suzhou: Explainable AI forecasting with longitudinal data and multi-stage rolling validation” (苏州市姑苏区功能重构与空间提质的长期消长：长时序可解释智能预测与多阶滚动验证) has been accepted by Urban Development Studies (城市发展研究)!
  • [2026-10] Our paper “Generative AI for urban planning: designing streetscapes from street-view imagery using diffusion models” has been accepted by Environment and Planning B: Urban Analytics and City Science !
  • [2026-10] Our paper “US Nationwide Travel Mode Detection Using GPS Data” has been accepted by Transportation !
  • [2026-10] My co-corresponding-authored paper “Urban Visual AI for Travel Behavior Prediction: A Comparative Analysis of Satellite and Street View Imagery” has been accepted by Journal of Transport and Land Use !
  • [2026-10] Our paper “Impacts of subway line extension on economic vitality and social cohesion: Evidence from Boston’s Green Line Extension through a double machine learning DID approach” has been accepted by Transportation Research Part A: Policy and Practice !
  • [2026-09] Our paper “Forecasting of future electric-vehicle charging demands for unravelling city-scale carpark photovoltaic charging capacity” has been accepted by Travel Behaviour and Society !
  • [2026-06] My corresponding-authored paper “Transit-Oriented Land Use Planning for Regional Metro Networks via Deep Reinforcement Learning” has been accepted by Transportation Research Part A: Policy and Practice !
  • [2026-01] My co-first authored paper “UrbanControlNet: Reimagining Global Urban Development with Satellite Imagery” has been accepted by the 2nd Workshop on AI for Urban Planning (AI4UP) at AAAI 2026 !
  • [2025-10] My first-authored paper “Analyzing sequential activity and travel decisions with interpretable deep inverse reinforcement learning” has been accepted by Travel Behaviour and Society !
  • [2025-10] My corresponding-authored paper “Human-Guided Urban Form Generation Using Multimodal Diffusion Models” has been accepted by Building and Environment !
  • [2025-09] Our paper “RouteKG: A knowledge graph-based framework for route prediction on road networks” has been accepted by IEEE Transactions on Intelligent Transportation Systems !
  • [2025-09] Our paper “Generative AI for urban planning: Synthesizing satellite imagery via diffusion models” has been accepted by Computers, Environment and Urban Systems !
  • [2025-09] I am deeply honored to receive the prestigious Li Ka Shing Prize for HKU Research Postgraduate Students 2023–24, awarded annually to up to four PhD theses in recognition of academic excellence.
  • [2025-03] Our paper “Architectural design and building-level infections during the early stage of COVID-19: A study of 2597 public housing buildings in Hong Kong” has been accepted by Building and Environment !