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About

Zhenliang Zhang is a pioneering researcher at the intersection of robotics, virtual reality (VR), and human-robot interaction, with a focus on building intelligent, interactive agents that seamlessly bridge the physical and virtual worlds. His major contributions center on the development of **Symmetrical Reality (SR)** systems—a novel framework where humans and virtual or physical robots coexist and collaborate within a shared mixed-reality environment. Zhang’s most influential work, **VRGym** (25 citations), introduced a VR testbed for training both physical and interactive agents, emphasizing realistic human-robot interaction for robotics and cognitive science. He further advanced the field with a graph-based hierarchical knowledge representation method (17 citations), enabling complex robot task transfer from virtual demonstrations to physical robots, such as cloth-folding with a Baxter robot. His research rethinks human-robot collaboration by proposing symmetrical reality systems that treat both human and machine as perceptual centers, enhancing cooperative manipulation. With a total of over 50 citations across his top papers, Zhang’s work is foundational for next-generation embodied AI and mixed-reality robotics, offering practical pathways for training robots in safe, simulated environments before deploying them in the real world.