I have twenty years of experience working with spatial data (GIS and satellite data) and integrating them into mathematical models and image analysis work. In particular, I have experience assimilating spatial (GIS and Remotely Sensed data) and attribute data at different spatial and temporal scales and up/down-scaling spatial data for integration into mathematical models and validation of model output. I have taught graduate level GIS courses at three Universities on three continents. My teaching method is data-driven: my students have learned GIS by manipulating actual data pertaining to real problems of interest to them (found with my help as needed), thereby producing projects of value for their needs and interests, rather than working on toy problems lacking both relevance and limitations.
I earned a Ph.D. in Environmental Engineering (specializing in Hydrology) at Cornell University and a M.Sc. in Remote Sensing at the Rochester Institute of Technology. My postdoctoral training was at the National Oceanic and Atmospheric Administration (NOAA), where I was involved in calibration, validation, quality control-and-quality analysis (QC/QA) of remotely sensed sea surface data. I have worked on projects pertaining to hydrology, climatic effects on species, Species Distribution Models (SDM), Agent Base Models (ABM), spatial factors controlling disease transmission, landuse/landcover change, disaster management and monitoring, spatial resettlement patterns after a disaster, landscape dynamics (spatio-temporal analysis of remotely sensed data, spatio-temporal modeling of urban sprawl and human migration