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About

Greg Wayne is a leading researcher at the intersection of artificial intelligence, robotics, and motor control, whose work focuses on building artificial agents capable of natural, whole-body interaction with the physical world. His key research areas include imitation learning, physics-based character animation, and multimodal interactive intelligence. Wayne’s major contributions center on developing reusable neural controllers that enable humanoid agents to perform complex, vision-guided tasks—such as his landmark “Catch & Carry” system (98 citations), which solves the longstanding challenge of flexible, realistic object manipulation. He has also pioneered robust imitation learning methods (64 citations) that overcome cascading failures in motor control, and advanced the creation of interactive agents that combine language, vision, and physical action (43 and 32 citations). His work has been recognized for bridging graphics, robotics, and neuroscience, with notable achievements including the development of agents that can imitate diverse behaviors from limited data and interact with humans through natural language. With a growing citation impact, Wayne’s research is shaping the future of embodied AI, bringing science fiction visions of helpful, dexterous robots closer to reality.