Biography

Jinzhou Cao is an Associate Professor and master’s supervisor at the College of Artificial Intelligence, Shenzhen Technology University. He serves as Executive Director of the Spatiotemporal Intelligence Research Center and Deputy Head of the Department of Data Science. He received his Ph.D. from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, and was a visiting scholar at the University of Washington. Before joining SZTU, he worked at the Guangdong Key Laboratory of Urban Informatics, Shenzhen University, as a postdoctoral researcher and specially appointed associate research fellow.

His research focuses on spatiotemporal big data mining, urban computing, Geo-AI, multimodal urban foundation models, and human mobility analytics. He has led more than ten research projects funded by the National Natural Science Foundation of China, the China Postdoctoral Science Foundation, Guangdong Basic and Applied Basic Research Foundation, Shenzhen Natural Science Foundation, and open funds from key laboratories of the Ministry of Natural Resources. He has published more than 50 papers in journals and conferences including Information Fusion, ISPRS Journal of Photogrammetry and Remote Sensing, Computers, Environment and Urban Systems, International Journal of Geographical Information Science, Cities, AAAI, and ICASSP. Two papers are ESI Highly Cited Papers, and his work has received more than 1,500 Google Scholar citations. He holds 24 granted invention patents and 3 software copyrights, and received the First Prize of the Surveying and Mapping Science and Technology Award.

Download his resumé(En) or resumé(Ch).

Professional Appointments
  • Associate Professor; Executive Director of STIC; Deputy Head of Data Science, 2026.04-present

    College of Artificial Intelligence, Shenzhen Technology University

  • Assistant Professor; Deputy Head of Data Science, 2022.04-2026.03

    College of Artificial Intelligence, Shenzhen Technology University

  • Specially Appointed Associate Research Fellow, 2021.08-2022.03

    Guangdong Key Laboratory of Urban Informatics, Shenzhen University

  • Postdoctoral Fellow, 2019.07-2021.07

    Shenzhen University; advisor: Academician Qingquan Li

Education
  • Ph.D. in Engineering, urban data mining, 2013-2019

    LIESMARS, Wuhan University

  • Visiting Scholar, THINK LAB, 2017-2018

    School of Civil and Environmental Engineering, University of Washington

  • B.S. in Remote Sensing Science and Technology, 2009-2013

    School of Remote Sensing and Information Engineering, Wuhan University

Feel free to contact me directly or to schedule an appointment.

Research Directions

Urban spatiotemporal data sensing and representation

Urban Spatiotemporal Sensing

Integrating multi-source urban sensing data to represent spatial structure, functional semantics, and dynamic change.

Multimodal urban foundation models and applications

Multimodal Urban Foundation Models

Building multimodal representations and foundation models for urban understanding, prediction, and decision support.

Geospatial intelligence and social computing

Geo-AI And Social Computing

Combining Geo-AI, social sensing, and knowledge reasoning for urban governance and spatial decision-making.

Human mobility and travel behavior analytics

Human Mobility Analytics

Analyzing travel behavior, activity networks, and urban flows to support transport and planning applications.

Urban Spatial Intelligence Lab

Urban Spatial Intelligence Lab

The Urban Spatial Intelligence Lab is Prof. Jinzhou Cao's research group and is affiliated with the Spatio-Temporal Intelligence Center at Shenzhen Technology University. The lab works on urban intelligent computing, urban spatial representation, Geo-AI, multimodal urban sensing, and human mobility analytics.

Openings For Graduate And Senior Undergraduate Students Students with backgrounds in computer science, data science, GIS, remote sensing, urban science, Geo-AI, urban computing, or system development are welcome to join. View Openings

News

RAMEN: Region-Adaptive Mixture of Ego-Networks for Multimodal Geospatial Fusion in Urban Region Representation was published in Mathematics. Paper
UrbanMMCL was published in ISPRS Journal of Photogrammetry and Remote Sensing. Paper
Gave an oral presentation on multimodal urban sensing data-driven region representation at SpatialDI 2026. News
Delivered an invited talk at the first AI and GIS Interdisciplinary Workshop. News
Sat2Flow was published at AAAI 2026. Paper
Learning Fine-Grained Urban Mobility Dynamics Through Large Model-Enhanced Multimodal Representations was published in IEEE T-ITS. Paper
Started a Guangdong Basic and Applied Basic Research Foundation project on multimodal urban spatial representation. Project
Delivered invited talks on urban foundation models at SIAT and Peking University Shenzhen Graduate School. News
Presented work on multimodal urban foundation models at the 20th Annual Conference on GIS Theory and Methods. News
ST-camba was published in Information Fusion. Paper

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