About me

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Here is Xuanyu Zhou.

I am an undergraduate student in the Urban and Rural Planning at Zhejiang University. I’m also an exchange student in the College of Environmetal Design (CED) in University of California, Berkeley (UCB). My research focus on Urban Equity, Urban Mobility, Big data and Machine Learning in Urban Planning. I’m exploring LLM in Urban Planning and Urban AI.

I have publish some of my work in leading journals, including Transaction in Urban Data, Science, and Technology.

If you are interested in any aspect of me, I am always open to discussions and collaborations. Feel free to reach out to me at — xuanyu.zhou [at] zju.edu.cn or xuanyu.zhou [at] berkeley.edu

Download my CV (Update October 2025)

Research Interests

My research interests mainly focus on Data-driven Urban Planning, including:

Urban Equility: Applying demographic and visitation data to explore the equity of urban infrastructure, particularly through spatio-temporal analysis of urban green space (UGS) access and its impact on community resilience in shrinking cities.
Urban AI: Leveraging machine learning techniques, such as Geographically Weighted Random Forest (GWRF), to model complex urban phenomena—from post-pandemic resilience to the relationship between the built environment and public health outcomes.
LLM for Urban Planning: Exploring the application of Large Language Models to analyze urban policy documents, public sentiment, and qualitative data to generate insights for more responsive and inclusive planning strategies.
Urban Mobility: Developing advanced modeling frameworks for next-generation transportation systems, including shared mobility and Urban Air Mobility (UAM), integrating dynamic demand patterns and heterogeneous fleets to optimize for efficiency and equity.

News and Updates

Sep 2025: Work accepted by Transportation Research Board (TRB) Annual Meeting, see you in Washington, D.C.!
May 2025：Participate in MIT-UF-NEU Summer Research Camp, mentored by Xuan Jian, Ph.D.
November 2024：Very excited to participate in Association of Collegiate Schools of Planning (ACSP) annual meeting in Seattle. I’ll talk about my recent research on urban green space in shrinking cities.
Aug 2024: Work accepted by ACSP Conference, see you in Seattle!

Along the Way

My journey into urban research began in my sophomore year at Zhejiang University, where I was selected for the Qizhenwenxue Undergraduate Research Program. Under the guidance of Prof. Shuang Ma and Prof. Shuangjin Li, I first tackled pressing, real-world issues. My initial project analyzed post-pandemic urban resilience by using Geographically Weighted Random Forest (GWRF) to link built environment characteristics to recovery rates (published here). This experience honed my technical skills in R and foundational academic writing. I expanded on this theme by investigating the complex interplay between public health, shared mobility, and urban form, leading the data analysis and authoring key sections of a manuscript submitted to Transportation Research Part D.

Eager to delve deeper into data-driven urbanism, I joined the Natural AI Lab, led by Mingze Chen, in my junior year. There, I spearheaded a project examining the role of Urban Green Space (UGS) in the revitalization of shrinking cities. By conducting a time-lagged analysis of Pittsburgh, PA, I uncovered how UGS visitation patterns correlate with demographic resilience. I authored the full manuscript, which was presented at the prestigious 2024 ACSP Annual Conference and is now under review at Urban Forestry & Urban Greening.

Seeking a global perspective, I spent my senior year as an exchange student at UC Berkeley’s College of Environmental Design. While excelling in coursework, I seized the opportunity to contribute to cutting-edge research at the Prof. Lu Liang’s Monitoring-Mapping-Modeling (3M) lab at UC Berkeley, where I colliborate with Ph.D. student Yuye Zhou. Our work advanced urban modeling techniques by comparing LiDAR-based Sky View Factor (SVF) with traditional imagery-based methods, contributing new precision to microclimate analysis.

My trajectory culminated in the MIT-UF-NEU joint summer research camp, where I addressed the future of urban mobility. Supervised by Prof. Jinhua Zhao and collaborating with Xuan Jiang, I co-developed a sophisticated framework for optimizing Urban Air Mobility (UAM) systems. Our model, which integrates dynamic demand and heterogeneous fleets, was validated in a San Francisco Bay Area case study and has been submitted to top-tier venues, including the TRB Annual Meeting and IEEE Transactions on Intelligent Transportation Systems.

From public health and urban resilience to advanced geospatial modeling and next-generation transit, my research path has been a systematic exploration of how data and technology can be leveraged to create more equitable, sustainable, and livable cities. Each step has deepened my expertise and solidified my passion for tackling complex urban challenges. To continue this journey, I am eager to join a rigorous master’s program that will empower me to address these complex urban issues at a deeper level.