Summary
Ross Boczar is a quantitative researcher with a decade of experience applying control theory, machine learning, optimization, and game theory to real-world systems, currently researching trading strategies at Radix Trading. He earned a PhD in EECS from UC Berkeley under Ben Recht and followed with a postdoc at the University of Washington, blending rigorous theory with applied experiments. Prior industry roles at Amazon Go and Amazon Advertising saw him deploy ML and control solutions in production settings, while earlier positions in avionics and RF diagnostics reflect a strong hardware-to-software grounding. Ross combines deep mathematical tooling with hands-on engineering, comfortable moving from convex optimization theory to production ML pipelines—an uncommon breadth that accelerates research-to-deployment cycles.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (PhD), Electrical Engineering and Computer Science, Doctor of Philosophy (PhD), Electrical Engineering and Computer Science at University of California, Berkeley
B.S., M.S., Electrical Engineering, B.S., M.S., Electrical Engineering at University of Pennsylvania