Summary
Morteza Khazaei is a PhD researcher in remote sensing at Université de Sherbrooke with eight years of experience bridging web development, machine learning, and multi-source satellite data processing. He develops web-based geospatial systems in Python and applies advanced methods—now pioneering Deep Generative Models for radar-based surface soil moisture and roughness estimation—to make soil parameter retrievals more robust across sensors and environments. His background includes high-resolution soil moisture mapping, optical–spectroscopy synergies for soil organic matter, and operational deployments like Sen2Agri for crop mapping in Iran, reflecting both research and applied impact. He has led object-based Sentinel-2 time-series land cover methods and built end-to-end pipelines for drought indices and spatial databases, demonstrating full-stack geospatial engineering. Comfortable collaborating with agencies such as the Iranian Space Agency and national ministries, he combines academic rigor with production-grade tooling and cross-disciplinary partnerships. A subtle strength is his dual fluency in building scalable web platforms and in translating complex remote sensing theory into operational agricultural and hydrological products.
8 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD, Remote Sensing, Doctor of Philosophy - PhD, Remote Sensing at Université de Sherbrooke
Master's degree, Remote Sensing & GIS, Master's degree, Remote Sensing & GIS at University of Tehran
Bachelor's degree, Watershed Engineering, Bachelor's degree, Watershed Engineering at Malayer University