Todd Hester is a seasoned machine learning and robotics leader with 11 years of experience applying reinforcement learning, perception, and control to real-world systems. Currently on Waymo’s Sim Realism team, he focuses on bridging simulation and reality for autonomous behavior prediction after leading perception and RL for Amazon Scout sidewalk robots. Previously he ran a DeepMind–for–Google research team, managing 12 scientists to deploy ML across products from data-center cooling to recommender systems, and he holds a Ph.D. in computer science with a long history of robotics and control research. Todd’s background spans both research and product deployment—from Nest thermostat algorithms to robotics instruction and low-level embedded work—giving him a rare end-to-end perspective on building deployed ML systems. He’s known for translating advanced research (e.g., RL with expert demonstrations and multimodal sensor fusion) into production gains, and he’s based in Fort Collins, Colorado.
11 years of coding experience
20 years of employment as a software developer
Ph.D, Computer Science, Ph.D, Computer Science at The University of Texas at Austin
B.S, Computer Engineering, B.S, Computer Engineering at Northeastern University
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