Xueguang Jin

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About

Xueguang Jin is a pioneering researcher at the intersection of human-computer interaction, assistive robotics, and intelligent scheduling systems. Their most notable contribution is the development of the “Avatar to Person” (ATP) system, a virtual human social ability enhancement platform designed specifically for disabled individuals. This work, which has garnered 11 citations, addresses a critical challenge in the AI era: leveraging affective computing and big data to improve communication effectiveness for those with social or physical limitations. By integrating social robots and smartphone technologies, Jin’s research enables more inclusive social networks, bridging the gap between virtual avatars and real-world human interaction. More recently, Jin has advanced the field of multi-robot systems with a deep reinforcement learning approach to cooperative scheduling, based on a service entity network. This forward-looking work, published in 2025, promises to optimize complex coordination tasks in dynamic environments, with applications in logistics, manufacturing, and autonomous systems. Jin’s research is characterized by its human-centered focus, combining cutting-edge AI with practical solutions for societal benefit. Their work not only pushes the boundaries of robotics and affective computing but also demonstrates a profound commitment to enhancing quality of life through technology.