Rıdvan Salih
Research Lead - Efficiency In AI4EO at German Aerospace Center (DLR)
Germany
Summary
👤
Senior🎓
Top SchoolRıdvan Salih is a research lead and AI-for-Earth-Observation specialist with nine years of experience bridging computer vision, digital signal processing and resource-efficient machine learning for real-world applications in remote sensing, biometrics and aeronautics. He holds a PhD as a Marie Curie researcher on mobile biometrics (winner of the 15th European Biometrics Research Award) and now leads efficiency-focused AI research at DLR while advising Helmholtz on transportation and aeronautics. His work blends theoretical signal-transform and filter design with practical multispectral image processing, segmentation and localization—skills he applies to forest monitoring and food-security problems as well as vein/face/fingerprint privacy-preserving biometrics. A serial R&D founder and project lead, he has a track record of winning and managing EU- and national-funded research programs and turning academic ideas into deployed systems. Notably, his background in control and electronics (Boğaziçi and Roma Tre) gives him an uncommon systems-level view that ties low-level signal methods to scalable ML solutions.
9 years of coding experience
9 years of employment as a software developer
Master of Science - MS, System and Control Engineering, Master of Science - MS, System and Control Engineering at Boğaziçi University4.89/5, Science High School, 4.89/5, Science High School at Konya Meram Fen LisesiDoctor of Philosophy - PhD, Applied Electronics, Doctor of Philosophy - PhD, Applied Electronics at Università degli studi Roma TRE
English, Italian, Turkish, German
Github Skills (10)
convolutional-neural-networks10
radiant9
random-forest8
satellite-images8
vision-transformer7
planet7
earth7
deep-learning7
deep-neural-networks4
database1
Programming languages (3)
Github contributions (5)
ridvansalihkuzu/author-attribution
Mar 2017 - Jul 2022
Contributions:1 release, 32 commits, 25 pushes in 5 years 5 months
ridvansalihkuzu/vein-biometrics
Oct 2019 - Oct 2020
A State-of-the-art Solution for Finger-Vein, Palm-Vein, Dorsal-Vein Recognition by Using Deep Learning
Contributions:15 commits, 19 pushes, 1 branch in 1 year
deep-learningvein-biometricsvascular-biometricsbiometric-recognitiondorsal-vein-recognition
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