Yongze Song is an Associate Professor at Curtin University. His research advances geospatial artificial intelligence, spatial statistics, and remote sensing for sustainable infrastructure and Earth- and urban-system applications. 

He develops open-source methods and tools across spatial prediction and spatial machine learning, spatial heterogeneity and driver attribution, and urban analytics for spatial patterns, accessibility and decision-making. He has developed 45 geospatial methods and 12 open-source R packages with 260,000+ downloads, and published 160+ peer-reviewed journal articles including 10 ESI highly-cited papers, advancing interpretable and reproducible spatial analysis adopted across academia, government, and industry.

He is an Australian Young Tall Poppy Science Award winner, Royal Geographical Society Fellow (UK), Harvard Spatial Data Lab Fellow (US), DAAD AInet Fellow (Germany), and IAMG Committee Member, with further honours including the Geospatial World 50 Rising Stars, Global Top 10 Young Scientist Award, Stanford World's Top 2% Scientists, and the Australian National Location Data First Prize.

He is an Associate Editor or Editor of six international journals (including 3 Q1 journals: the International Journal of Applied Earth Observation and Geoinformation, GIScience & Remote Sensing, and Geoscientific Model Development), Editorial Board Member of 17 journals, Guest Editor of 20 special issues, Chair or Program Committee Member for 45 conferences, reviewer for 80+ journals, and has delivered 120+ invited seminars worldwide, including at Harvard, MIT, Yale, ANU, and NUS.