Orhun Aydin

I am an Assistant Professor in the Department of Earth and Atmospheric Sciences and Computer Science (by courtesy) at Saint Louis University. My research focuses on spatial machine learning (GeoAI) and geospatial sensor networks for computational sustainability and resilience. I use a variety of Earth observations, in-situ measurements, physical process models, and spatially-explicit artificial intelligence (now broadly known as GeoAI) to answer questions pertinent to sustainable development goals (SDGs) and resilient geodesign. I am particularly interested in spatial game theory, prescriptive learning, spatial optimization for disaster response, big geospatial data analysis, and graph-based representations of spatial data. In addition to GeoAI methods, I work on designing, developing, manufacturing, and installing low-cost geospatial sensor IoT networks for problems where limited or no data exists. If installing sensors are not feasible, I fly them on uncrewed aerial vehicles (UAVs). I operate multiple medium and heavy-lift UAVs in my lab and am a licensed drone pilot.

Prior to joining SLU, I served as research scientist and lead product engineer for the Spatial Statistics and R-ArcGIS Bridge teams at Esri, respectively. I worked on applied and theoretical research in spatial and spatio-temporal machine learning methods, their implementations in ArcGIS platform, and applications to climate change-related problems.

I believe in the power of spatial thinking and analysis for spatial problems and have been an ardent supporter of broad spatial science and Earth science education. Prior to my role at SLU, I served as a lecturer in the Geographic Information Systems program at Johns Hopkins University and at the University of Southern California’s Spatial Sciences Institute. My teaching focuses on geospatial and spatiotemporal statistics, machine learning in GIS and remote sensing, programming in GIS, and GeoAI for sustainability.