Ce Hou
δΎ―η
AI for Sustainable Urban Development
About
Hi, I'm Ce Hou π. I am currently a Ph.D. candidate at 
Hong Kong University of Science and Technology and a Visiting Scholar at 
Peking University, supervised by Prof. Fan Zhang and Prof. Sen Li. I received my Bachelor's degree from 
Wuhan University and my Master's degree from 
University College London. From March 2026, I start my journal as a Visiting PhD Student at 
University of California, Berkeley, working with Prof. Lu Liang. For more background information, please refer to my CV.
π¬ My research interest lies in: Leveraging urban multi-modal data and advanced AI methods (e.g., Large Language Models) to support sustainable urban development
Latest News
A new paper published in Transactions in Urban Data, Science, and Technology
A new paper published in Transactions in Urban Data, Science, and Technology
π Got one paper as first-author published in Transactions in Urban Data, Science, and Technology.
Arrived at UC Berkeley to Begin My Visiting Journey!
Arrived at UC Berkeley to Begin My Visiting Journey!
π I successfully arrived at the University of California, Berkeley (UC Berkeley), officially beginning my visiting journey. I look forward to embarking on a fulfilling and exciting research adventure here!
New preprint on VLM-Human Preference Alignment
New preprint on VLM-Human Preference Alignment
π A new co-authored preprint titled 'UrbanAlign: Post-hoc Semantic Calibration for VLM-Human Preference Alignment' is available on arXiv.
I was elected as CPGIS BOD Student Member!
I was elected as CPGIS BOD Student Member!
π³οΈ Honored to be elected as a Student Member of the Board of Directors (BOD) for CPGIS. Thank you to everyone who has supported me. Looking forward to serving the global GIS community!
Received Overseas Research Award
Received Overseas Research Award
π Honored to receive the Overseas Research Award from the Hong Kong University of Science and Technology.
Deciphering exterior: building energy efficiency prediction with emerging urban big data
Deciphering exterior: building energy efficiency prediction with emerging urban big data
TBD
Authors: Maoran Sun, Ce Hou, Qiaosi Li, Fan Zhang, Ronita Bardhan, Qunshan Zhao*
Multi-source geo-localization in urban built environments for crowd-sourced images by contrastive learning
Multi-source geo-localization in urban built environments for crowd-sourced images by contrastive learning
A contrastive learning approach for multi-source geo-localization in urban built environments.
Authors: Qianbao Hou, Ce Hou, Fan Zhang, Qihao Weng*
Urban sensing in the era of large language models
Urban sensing in the era of large language models
TBD
Authors: Ce Hou, Fan Zhang*, Yong Li, Haifeng Li, Gengchen Mai, Yuhao Kang, Ling Yao, Wenhao Yu, Yao Yao, Song Gao, Min Chen, Yu Liu
Transferred bias uncovers the balance between the development of physical and socioeconomic environments of cities
Transferred bias uncovers the balance between the development of physical and socioeconomic environments of cities
TBD
Authors: Ce Hou, Fan Zhang*, Yuhao Kang, Song Gao, Yong Li, FΓ‘bio Duarte, Sen Li
Skills
Internship & Work Experience
University of California, Berkeley
Peking University
Tsinghua University
The Bartlett School of Sustainable Construction, UCL
Awards & Honors
Overseas Research Award, HKUST
Best Poster Award, the 2nd Research Summit of Urban Science and Human Dynamics
Creativity Award, Research Summit of Urban Science and Human Dynamics
Bezos/Musk Prize for Entrepreneurial Potential in Knight Frank Dubai Housing Data Hackathon
Outstanding Graduate Student, Wuhan University
Academic Services
Chinese Professional in Geographic Information Systems
GISPhere
Chinese Professional in Geographic Information Systems
Introduction to Smart City Economics (CIVL4640)
Geospatial Science & Technology for Smart City (CIVL4100U)
Invited Talks
GISense Lab at the University of Texas at Austin
GISense Lab at the University of Texas at Austin
Leveraging GeoAI and LLM for sensing the sustainable urban development
China University of Geosciences (Wuhan)
China University of Geosciences (Wuhan)
Transferred bias uncovers the balance between the development of physical and socio-economic environments of cities
Center for the Built Environment, University of California, Berkeley
Center for the Built Environment, University of California, Berkeley
Street View Imagery as a Lens for Sensing Buildings
Get in Touch
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