Designing data‑driven tools for fairer urban futures.
I’m Xuanyu Zhou. I trained as a planner at Zhejiang University, spent a semester at UC Berkeley’s College of Environmental Design, and now study at Penn. My research asks who gets the good parts of a city — shade, green space, quick trips, a fast recovery after a crisis — and measures it with remote sensing, simulation, and machine learning. Lately I’m also testing where LLMs are genuinely useful in planning work.
Research
All publications →-
01
Mobility systems
Simulation-first frameworks for urban air mobility and shared mobility, tested against real metropolitan demand.
-
02
Street microclimate
Pedestrian-scale sky view factor, estimated from LiDAR and street-level imagery and mapped along San Francisco’s sidewalks.
-
03
Green space & equity
Who has green space and who actually uses it, tracked with satellite imagery and visitation data in shrinking cities.
-
04
Resilience & health
Geospatial machine learning that links urban form to post-pandemic recovery, everyday vitality, and public health.
On my desk
Everything here is a link — hover the laptop for selected work. Everything here is a link — tap any object to open it.
News
-
Started the Master of City Planning program at the University of Pennsylvania Weitzman School of Design.
-
Submitted a systematic review of 1,446 planning studies to Landscape and Urban Planning as corresponding author.
-
Presented PedSVF: Multimodal Aerial–Street Grounding for Pedestrian-Scale Sky View Factor Estimation at Geoinformatics 2026, National University of Singapore.
-
Graduated from Zhejiang University as an Outstanding Graduate, with an Outstanding Undergraduate Thesis award.