Doctoral Researcher at CISPA Helmholtz Center for Information Security
Cologne, North Rhine-Westphalia, Germany
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Summary
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Senior
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Soroush Zargarbashi is a PhD researcher focused on Trustworthy AI, specializing in robustness and uncertainty quantification for machine learning models, particularly Graph Neural Networks. Based at CISPA and affiliated with the University of Cologne, he has authored multiple high-profile conference papers (ICML, ICLR) on robust and conformal prediction methods and adversarial graph attacks. His background spans applied research and engineering—from evolutionary attacks on graphs and optimal conformal prediction to building Django-based microservices for quantitative trading—bridging theoretical innovation with practical systems. He also interned on speech translation and LLM/speech encoding at Apple, reflecting experience across modalities. With a decade of experience and a trajectory that connects epigenetic data analysis to cutting-edge AI safety work, he brings a rare mix of mathematical rigor and production-minded engineering.
10 years of coding experience
Doctor of Philosophy - PhD Artificial Intelligence, Doctor of Philosophy - PhD Artificial Intelligence at University of Cologne
Master's degree Computer Science / Artificial Intelligence, Master's degree Computer Science / Artificial Intelligence at University of Tehran
Bachelor’s Degree Computer Software Engineering, Bachelor’s Degree Computer Software Engineering at Isfahan University of Technology
Doctor of Philosophy - PhD Trustworthy AI, Doctor of Philosophy - PhD Trustworthy AI at CISPA Helmholtz Center for Information Security
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Soroush Zargarbashi - Doctoral Researcher at CISPA Helmholtz Center for Information Security