Ph.D. (Civil and Environmental Engineering), University of New South Wales, Sydney, NSW, Australia.
M.A. (Cartography and Geographic Information System) East China Normal University, Shanghai, China.
B.A. (Geographic Information System) East China Normal University, Shanghai, China.
Dr. Bingnan Li is a Research Associate (research-focused academic staff) in the Biosecurity Program of Kirby Institute, Faculty of Medicine and Health, UNSW Sydney. He holds a Ph.D. degree in Geospatial Data Mining from the School of Civil and Environmental Engineering, Faculty of Engineering at UNSW, and a Master degree in Geographical Information Systems (GIS) from East China Normal University, Shanghai, China. Under the supervision of A/Prof. Samsung Lim, his Ph.D. research is focused on deep learning-based spatio-temporal data mining using multi-source geospatial data. He proposed four efficient approaches in different scenarios for spatio-temporal data mining that take advantage of multi-source geospatial data to overcome the limitations of traditional data mining methods. He also applies GIS to real-world problems and helps decision-making, including red-flagging of epidemics. His research fields include geospatial analysis, geospatial data mining, and social media analysis of infectious diseases.