I'm Islam, a postdoctoral researcher working on AI-based Earth observation โ combining machine learning with physical models to extract geophysical parameters from SAR and optical satellite data.
I completed my Bachelor's degree in Aerospace Engineering at Istanbul Technical University in 2017, then worked as a System & Software Engineer at Bosch on automated driving functions and model-based testing.
In 2018, I moved to Munich to pursue a Master's in Earth Oriented Space Science and Technology (ESPACE) at the Technical University of Munich, working on multi-frequency polarimetric SAR over permafrost regions, with internships at Remote Sensing Solutions GmbH and Airbus Defence and Space.
From 2021 to 2025, I did my PhD at DLR's Microwaves and Radar Institute and ETH Zรผrich's Chair of Earth Observation and Remote Sensing, building hybrid AI-physical models that combine data-driven learning with electromagnetic scattering models โ for forest height retrieval from TanDEM-X InSAR, penetration bias correction in X-band InSAR DEMs over Greenland, and TanDEM-X/GEDI synergy for forest structure mapping across the Brazilian Amazon. I also co-developed the DLR/ESA PolInSAR Training Course infrastructure on ESA's MAAP platform.
Since April 2025, I've been a postdoctoral researcher at the Universitรคt der Bundeswehr Mรผnchen (UniBW), developing AI-based Earth observation methods that lean on foundation models for SAR and optical data: adapting large vision foundation models to remote sensing tasks, building a hybrid ship detection and segmentation system (YOLO11 + SAM2) for maritime surveillance, and generating OpenStreetMap-style vector maps from very-high-resolution optical imagery.
Synthetic Aperture Radar (SAR) and InSAR, forest height and biomass retrieval, hybrid physics-informed machine learning, multi-mission data synergy (TanDEM-X, GEDI, Sentinel-1), and foundation models for Earth observation โ and, where it all started, space technology and embedded systems.
I use to manage my dot-files, which includes various configuration files for tools I use on a daily basis. This optimization of my workflow allows me to quickly and easily configure my environment on any machine I work on. Check out my
to see my configurations.
If you'd like to learn more about my work or discuss potential collaboration opportunities, feel free to connect with me on LinkedIn or drop me an email. I am always interested in connecting with fellow researchers, engineers, and space enthusiasts!


