Summary
Orhan Ocal is a quantitative researcher based in Berkeley with 11 years of experience bridging academic signal-processing research and production quantitative engineering at Citadel Securities. A PhD candidate in EECS at UC Berkeley and MSc graduate from EPFL, he specializes in coding theory, signal processing and indoor localization, with internship work spanning voice conversion, beamforming for radio astronomy and acoustic source tracking. He has repeatedly translated research prototypes into practical algorithms—e.g., randomized beamforming to boost sparse recovery and neural autoencoder approaches for non-parallel voice conversion—demonstrating strength in both theory and applied systems. At Berkeley he contributed to course design and lab development for large-scale undergraduate offerings, earning an Outstanding Course Development award. Comfortable in C++ and ML stacks, he combines rigorous mathematical grounding with hands-on implementation experience across industry and academia.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD), Electrical Engineering and Computer Sciences, Doctor of Philosophy (PhD), Electrical Engineering and Computer Sciences at University of California, Berkeley
Bachelor of Science (BS), Electrical and Electronics Engineering, Bachelor of Science (BS), Electrical and Electronics Engineering at Boğaziçi Üniversitesi
Science Program, Science Program at Robert College
Master of Science (MSc), Communication Systems, Master of Science (MSc), Communication Systems at Ecole polytechnique fédérale de Lausanne
Electronics Engineering, Electronics Engineering at Istanbul Technical University
English