Rate My Professor Yongze Song

Yongze Song is an Associate Professor in the School of Design and the Built Environment at Curtin University, Perth, where he heads the Geospatial Intelligence Lab. He earned his PhD from Curtin University in 2018, receiving the Chancellor Commendation Award for an exceptionally high standard thesis and the Chinese Government Award for Outstanding Self-Financed Students Abroad. Prior to his doctorate, he obtained B.S. and M.S. degrees in surveying and mapping from China University of Geosciences (Beijing). Song's research specializations include spatial statistics, mathematical geosciences, remote sensing, urban science, and geospatial artificial intelligence. He has developed over 30 innovative geospatial methods, such as Degree of spatial interpretability, Geocomplexity, Second-Dimension Spatial Association, and Optimal Parameters-based Geographical Detectors, along with 12 R software packages that have garnered more than 200,000 downloads. His work applies Earth observation, AI, and big data to environmental monitoring, infrastructure maintenance, and urban sustainability.

Song's career at Curtin University progressed from PhD researcher (2015-2018) to Senior Lecturer (2023-2025) and Associate Professor (2025-present). He has received major awards including the Australian Young Tall Poppy Science Award (2025), Research Excellence Award for Early Career Researcher (Curtin University, 2023), Global Impact Award (Curtin University, 2024), World’s Top 2% Scientists (Stanford University, 2023 and 2024), Geospatial World 50 Rising Stars (2023), Fellow of the Royal Geographical Society (UK, 2020), DAAD AInet Fellow (Germany, 2023), and SDL Fellow (Harvard University, 2024). He holds editorial positions as Associate Editor for International Journal of Applied Earth Observation and Geoinformation and GIScience & Remote Sensing, and has chaired the ISPRS Technical Commission IV Symposium (2024) and City+2023 International Conference. With over 6,473 citations, key publications include "An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis" (2020, 1,245 citations, GIScience & Remote Sensing), "Trends and opportunities of BIM-GIS integration in the architecture, engineering and construction industry" (2017, 344 citations, ISPRS International Journal of Geo-Information), and "Observed inequality in urban greenspace exposure in China" (2021, 285 citations, Environment International). Song's contributions advance geospatial methodologies and their applications in sustainable development.