Yingchi Li

National Taiwan University of Science and Technology

Papers

Total Citations

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About

Yingchi Li is a robotics researcher whose work bridges computer vision, human-robot interaction, and autonomous systems for real-world applications. Her key research areas include mobile robotics, face recognition in dynamic environments, and preference-based learning for robot task alignment. In her early work, Li developed an integrated multipose face tracking and recognition system mounted on unmanned aerial vehicles for search and rescue operations, addressing the challenge of complex, dynamic disaster terrains. Her 2015 paper on this system has garnered 4 citations, demonstrating foundational contributions to field robotics. More recently, Li introduced FARPLS (Feature-Augmented Robot Trajectory Preference Labeling System), a novel approach to assist human labelers in preference elicitation for robot task learning. This 2024 work tackles the critical challenge of aligning robot objectives with human values through pairwise trajectory comparisons, offering enhanced support for labelers to identify and digest complex trajectory features. Li’s research represents an important step toward more intuitive human-robot collaboration, making her work valuable for students and researchers interested in autonomous systems that can learn from and respond to human preferences in real-world environments.