Liping Zhao

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About

Liping Zhao is a pioneering researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a specialized focus on the automatic aesthetic evaluation of robotic movements. Her work addresses a fundamental challenge in social robotics: enabling machines to perceive and generate motions that humans find visually pleasing. Zhao’s major contribution lies in developing computational frameworks that mimic human aesthetic cognition—particularly how dancers use visual feedback to refine their poses. Her most cited paper, "Feature fusion based automatic aesthetics evaluation of robotic dance poses" (2018, 14 citations), introduced a novel method that fuses multiple features to assess robotic dance, laying the groundwork for more human-like robot choreography. She further advanced this field with her hierarchical processing network (2022, 4 citations), which models the layered visual perception humans use when judging dance aesthetics. Zhao’s research has direct implications for entertainment robotics, assistive technologies, and creative AI, demonstrating how machines can learn artistic judgment. Her work is increasingly cited in studies on affective computing and robot motion planning, marking her as a key voice in making robots not just functional, but expressive and aesthetically aware.