Wen Zhou

Wen Zhou

she/her

Postdoctoral scholar of University of Illinois Urbana Champaign

Welcome to Wen Zhou’s Homepage

I am a Postdoctoral Research Associate at the University of Illinois Urbana-Champaign, Department of Geography and GIS. I completed my Ph.D. in Remote Sensing and Earth Observation, where I developed innovative approaches for urban livability assessment and building functional analysis using multi-modal deep learning methods.

My research primarily focuses on GIS, GeoAI, especially multi-modal spatiotemporal data fusion, and their methodological and applied studies, addressing challenges related to urban resilience, environments, and sustainable development goals.

Education

  • Ph.D. in Remote Sensing and Earth Observation, University of Twente (2023)
  • M.Sc. in Geoinformatics, China University of Geosciences (Beijing) (2018)
  • B.Sc. in Geographic Information Science, China University of Geosciences (Beijing) (2015)

Research Interests

My research focuses on the intersection of urban geography, GeoAI, and geospatial data analysis. I am particularly interested in:

  • Flash Flood prediction: Predicting flood depth based on multiple geospatial data using GeoAI.
  • Urban Livability Assessment: Developing comprehensive frameworks to evaluate and measure urban quality of life using multiple data sources
  • Building Functional Analysis: Extracting and analyzing building use patterns from various geospatial datasets
  • Deep Learning Applications: Applying multi-modal deep learning techniques to urban research problems
  • Geospatial Data Integration: Combining remote sensing, GIS, and other spatial data for urban analysis
  • Mixed-Use Building Classification: Advanced methods for identifying and classifying complex urban building functions

Recent News

[2025.08] Leading a project about “Predicting and Mapping Floods through Geospatial Data Fusion and Machine Learning” in I-GUIDE Summer school 2025. This project focuses on developing advanced methodologies for flood prediction and mapping using geospatial data fusion and machine learning techniques.

[2025.07] Attending USGS 2025 CEGIS Annual Research Meeting. Giving an oral presentation about “Machine learning for urban flood inundation mapping”.

[2025.07] Serving as one of the Guest Editors for a Special Issue in Remote Sensing (MDPI) Innovations in Remote Sensing Image Analysis, focusing on cutting-edge developments in remote sensing image analysis.

[2025.06] Attending I-GUIDE Forum 2025. Giving an poster presentation about “Uncovering the impact of building spatial-functional information on urban livability using machine learning”.

For more detailed news and updates, please visit the News page.

Selected Publications

[2024] Zhou W, Persello C, Stein A. Hierarchical building use classification from multiple modalities with a multi-label multimodal transformer network[J]. International Journal of Applied Earth Observation and Geoinformation, 2024, 132: 104038.

[2023] Zhou W, Persello C, Li M, Stein A. Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information[J]. Remote Sensing of Environment, 2023, 297: 113767.

[2020] Zhou W, Ming D, Lv X, et al. SO–CNN based urban functional zone fine division with VHR remote sensing image[J]. Remote Sensing of Environment, 2020, 236: 111458.

For more detailed news and updates, please visit the Publications page.

Awards

  • HDR NextGen Leaders Fellowship (2025)
  • Excellent Master’s Degree Thesis Award of China University of Geoscience (Beijing) (2019)
  • Excellent Graduates Award of Beijing (2019)
  • Excellent research achievement award of CUGB (2018)