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About

He Wang is a robotics and computer vision researcher whose work spans embodied AI, simulation environments, multi-robot systems, and physical reasoning. He is perhaps best known for his foundational contribution to SAPIEN, a simulated part-based interactive environment designed to advance home assistant robotics research. Published in 2020, SAPIEN has amassed over 370 citations, reflecting its significant influence on the robotics and vision communities by providing physically realistic simulation with articulated objects transferable to real-world systems. Wang's research extends into multi-robot coordination, where his neural bipartite graph matching approach to active mapping addresses efficient scene reconstruction using multiple autonomous agents. His curiosity about machine physical reasoning is evident in work on predicting 3D object dynamics for unseen instances, a capability critical for building more adaptive robots and interactive virtual environments. More recently, Wang has explored the integration of large language models into robotics through RoboGPT, pushing toward embodied agents capable of long-term planning from natural language instructions. Across agricultural robotics, Wang has also contributed smooth trajectory planning for fruit-picking manipulators, demonstrating a versatile research portfolio bridging simulation, coordination, physical reasoning, and intelligent decision-making in robotic systems.