My name is Andy Jingqian Xue (θζ―θ°¦), and I am currently a PhD student at the School of Geography and Ocean Science, Nanjing University, under the supervision of Prof. Clive Eric Sabel. Prior to this, I earned my MPhil degree in Urban Governance and Design from the Hong Kong University of Science and Technology (Guangzhou), where I was supervised by Prof. Bin Jiang at LivableCityLAB. I received my BSc degree in Geographic Information Science from the School of Geography and Planning, Sun Yat-sen University.
I am deeply interested in the fundamental properties and patterns of geographic features. Consequently, I have developed several GeoAI algorithms that enable models to better learn complex spatial patterns or the so-called spatial heterogeneity, thereby improving the accuracy and model explicability of land use mapping. I am also studying and researching quantitative approaches to modeling urban complexity and spatial patterns. I firmly believe and advocate that the problems of cities lie not only in understanding spatial complexity but also in creating organized complexity to make cities more livable and resilient.
In addition to GeoAI and urban complexity, I am also interested in big data analysis and visualization, human perceptions of urban environments, and urban health. If you are interested in my experiences, please feel free to reach out through andy.j.xue AT hkust-gz.edu.cn.
Urban Complexity
The new kind of complexity from the living structure perspective that bridges space and mind.
Explainable AI
Explore how transformer models learn geospatial patterns from remote sensing imagery.
Paper Sharings
Follow me on Xiaohongshu, where I share iconic papers on complexity science, urban science, and more.
π Education
- 2025.09 - Present, PhD in Human Geography, School of Geography and Ocean Science, Nanjing University, Nanjing, China.
- 2023.09 β 2025.07, MPhil in Urban Governance and Design, Society Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China.
- 2019.09 β 2023.06, BSc in Geogrpahic Information Science, School of Geography and Planning, Sun Yat-sen University, Guangzhou, China.
π¨βπ« Teaching Experience
- Teaching Assistant, UGOD 5105 Urban Complexity and Modelling, HKUST(GZ), Spring 2025
π Publications
- Xue J. (2025), Characterizing Architectural and Urban Beauty from the Perspective of Living Structure Using AI and Geospatial Big Data, M.Phil. Thesis, The Hong Kong University of Science and Technology (Guangzhou): Guangzhou, China.
- Xue J. , Zhang Z., Zhou Y., Yuan L., He D. and Liu X. (2025), Geographic prior guided sub-pixel mapping for fine-grained urban tree covers reconstruction, IEEE Geoscience and Remote Sensing Letters, 22, 1β5.
- Xue J., Huang C. and Jiang B. (2024), Measuring global urban complexity from the perspective of living structure, Urban Informatics, 3(1), 1β15.
- Xue J., He D., Liu M. and Shi Q. (2022), Dual network structure with interweaved global-local feature hierarchy for transformer-based object detection in remote sensing image, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 6856β6866.
- He D., Shi Q., Xue J., Atkinson P. M. and Liu X. (2023), Very fine spatial resolution urban land cover mapping uUsing an explicable sub-pixel Mapping Network, Remote Sensing of Environment, 299, 113884 (ESI Highly Cited Paper).
- Shi Q., He D., Liu Z., Liu X. and Xue J. (2023), Globe230k: A benchmark dense-pixel annotation dataset for global land cover mapping, Journal of Remote Sensing, 3, 0078.
π¬ Conference Presentations
- Xue J., Huang C. and Jiang B. (2024), Measuring global urban complexity from the perspective of living structure, in Asian Cartographic Conference, International Cartographic Association: Hong Kong SAR, China (Best Student Paper Presentation Award).
- Huang C. and Xue J. (2024), Walking over the land: Mapping low-altitude accessibility using urban big data, in The ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiCompβ24), ACM: Melbourne, Australia (Student Challenge Project).
- He D., Shi Q., Xue J. and Liu X. (2024), Explicable sub-pixel mapping based on nested self-attention network with spatial correlation learnable mechanism, in International Geoscience and Remote Sensing Symposium, IEEE: Athens, Greece.