Ian Pegg is an Autonomy Engineer in San Diego with eight years of experience bridging machine learning research and safety-critical transportation systems. Currently completing a master's focused on deep reinforcement learning in non-stationary environments, he applies those techniques to real-world autonomy at Brain Corp and to research problems such as a refractive-layer Pong proxy for underwater communication. His background in engineering physics and hardware design (including SIL4 train control systems and IC test automation) gives him a rare blend of theoretical ML skill and hands-on electronics/testbed expertise. He has a track record of shipping reliable systems under field constraints, from urban rail deployments to automated test libraries, and enjoys turning complex physical constraints into tractable learning problems.
8 years of coding experience
1 year of employment as a software developer
University of California, San Diego
Bachelor of Science - BS, Engineering Physics, Electrical Option, 3.6 GPA, Bachelor of Science - BS, Engineering Physics, Electrical Option, 3.6 GPA at Queen's University
Contributions:80 commits, 2 PRs, 61 pushes in 1 month
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