Urban Computing · Urban Planning · Smart and Sustainable Mobility
Zeyu Wang
Ph.D. Candidate
Explore my workHi, I'm Zeyu!
Dynamic researcher with 6+ years of experience leveraging spatiotemporal data and advanced analytical technologies to analyze and improve urban spaces and human movement.
Dedicated to enhancing quality of life and promoting social equity through innovative solutions.
Proven ability to collaborate within interdisciplinary teams, adopting cutting-edge tools to tackle complex challenges.
Passionate about connecting with diverse individuals, enriched by experiences from traveling to over 40 countries and 100+ cities worldwide.
Bio
I'm a third-year Ph.D. student inUrban Design & Planning Interdisciplinary Ph.D. Programat theUniversity of Washington. Prior to that, I worked in theUrban Analytics Labat theNational University of Singapore, where I received my M.U.P. degree in Urban Analytics.
My research integrates advanced artificial intelligence and machine learning techniques to develop data-driven solutions for urban systems. I am fortunate to be advised byDr. Don MacKenzie(UW),Dr. Filip Biljecki(NUS),Dr. Jon E. Froehlich, andDr. Qing Shen.
I enjoy hiking, traveling, photography and proud of being a fan of aviation and transit. I am always eager to explore new places and cultures.
For more updates and further information about my featured past/ongoing research, please visit the research page.
Selected publications
Recent Work
News
- Presented at The 4th ACM SIGSPATIAL International Workshop on Spatial Big Data and AI for Industrial Applications (Minneapolis, MN): Street View for Whom?.
- Presented at TRB 104th Annual Meeting (Washington DC): Examining Household and Travel Dynamics in Response to Urban Visual Diversity Using Street View Images.
- Presented at ACSP 2024 Annual Conference (Seattle, WA): Physical Urban Change and Its Socio-Environmental Impact: Insights from Street View Imagery.
- Presented at Metrolab Summit 2024 (Washington DC): Using INRIX data to calibrate agent-based transportation models like POLARIS across multiple dimensions.
- Presented at International Association of China Planning 2024 Annual Conference (Hangzhou, China): Assessing Built Environment Perceptions in Urban Neighborhoods using Time-series Street View Imagery.