Summary
Salim Soltani is a remote sensing researcher with eight years of experience applying geospatial analysis, machine learning, and computer vision to environmental and biodiversity challenges. Currently a researcher at University of Freiburg and a PhD candidate at Leipzig University, he focuses on fusing citizen science imagery, UAV and satellite data with deep learning to map plant species at high resolution. His background includes applied roles at UN Environment and DLR, where he translated climate and terrain datasets into operational GIS products and capacity-building programs. Salim combines rigorous academic training from Würzburg and Leipzig with hands-on image analysis in industry projects like Invekos, giving him both research depth and operational delivery experience. He is an advocate for open-source tools and inclusive science, often leveraging crowd-sourced platforms such as iNaturalist to improve model transfer between ground photos and remote sensing. Notably, his work explores the non-obvious synergy between citizen science labels and large-scale remote sensing models to scale species mapping across heterogeneous landscapes.
8 years of coding experience
5 years of employment as a software developer
Fellowship, GIS/Remote Sensing/IWRM, Fellowship, Fellowship, GIS/Remote Sensing/IWRM, Fellowship at German Kazakh University of Kazakhstan
Habibia High school
PhD candidate, Remote Sensing, PhD candidate, PhD candidate, Remote Sensing, PhD candidate at Leipzig University
Bachelor of geoscience, GIS, Bachelor of geoscience, GIS at Bamyan university
Master's degree, Remote Sensing and GIS, Master's degree, Remote Sensing and GIS at The Julius Maximilians University of Würzburg
English, German, dari /persian, Pashto