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About

Cody Fong is a robotics researcher specializing in deep reinforcement learning, robotic manipulation, and the real-world deployment of intelligent autonomous systems. His most recognized work centers on scaling deep RL to practical, large-scale environments — most notably demonstrated in his highly cited 2023 paper on sorting recyclables and trash in office buildings using a fleet of mobile manipulators. This research, garnering 15 citations, tackled one of the field's most persistent challenges: bridging the gap between laboratory-trained policies and reliable real-world performance, addressing critical issues such as policy bootstrapping and scalable deployment infrastructure. Fong's work extends into the frontier of multimodal AI applied to physical agents. His contribution to the 2025 "Gemini Robotics" report reflects his engagement with cutting-edge efforts to translate the remarkable generalist capabilities of large multimodal models into embodied robotic systems — a challenge widely regarded as one of AI's most significant open problems. Taken together, Fong's research positions him at the exciting intersection of deep learning, robotics, and real-world AI deployment, making meaningful contributions toward robots that can function reliably and intelligently in everyday human environments.