Orhun Aydin, Ph.D., is a lecturer in the JHU Geographic Information Systems program. He teaches AS.430.603 Geospatial Statistics and AS.430. 633 Advanced Spatio-Temporal Statistics. He is also a researcher in Esri’s Spatial Statistics team where he conducts research into spatial and spatio-temporal tools and he is the product engineer for R-ArcGIS Bridge.
His research interests pertain to forecasting and understanding Earth systems via spatial and spatio-temporal statistical models. His theoretical work involves developing general mathematical frameworks for modelling, mining and representing spatial and spatio-temporal data. In particular, he researches graph-based methods to represent spatial data in machine learning applications. His applied research combines computer vision, machine learning, spatial statistics and Earth process models to develop domain-knowledge driven machine learning methods for modelling Earth processes under uncertainty and sparse data.