Liying Li
Papers
5
Total Citations
20
H-Index
3
About
Liying Li is a rising researcher at the intersection of human-robot interaction (HRI) and teleoperation, with a focus on how people perceive and interact with robotic systems—particularly quadruped robots like Boston Dynamics’ Spot. Her work explores three key areas: motion-controlled robotic arm systems for remote teleoperation, 3D human pose estimation from a robot’s perspective, and the social dynamics of robot movement and proxemics. Li’s most cited paper, “Toward Verifying the User of Motion-Controlled Robotic Arm Systems via the Robot Behavior” (2021, 12 citations), investigates how a robot’s own actions can authenticate its human operator—a novel approach to security in teleoperation. She also introduced the HARPER dataset (2024), the first to capture 3D body pose data from a robot’s onboard sensors during dyadic interactions, enabling advances in pose estimation and forecasting for HRI. Her recent work on quadruped gait perception and dynamic proxemics (2024–2025) reveals how robot locomotion style and spatial behavior shape human trust and comfort. With publications spanning 5G-enabled education and canine-inspired robotics, Li is building a foundation for more intuitive, socially aware robots in healthcare, remote training, and beyond.
Research Focus
Key Achievements
Top Papers
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- 3Towards 5G-Enabled Education: Remote Laboratory and Training Prototype3 citations · 2021
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