Chuxuan Yang
Papers
1
Total Citations
7
H-Index
1
About
Chuxuan Yang is a researcher in robotics and human-robot interaction, with a primary focus on Learning from Demonstration (LfD) and hierarchical task abstraction. Her work addresses a critical challenge in robotics: enabling non-expert users to teach robots complex, long-horizon tasks by leveraging the hierarchical structure of human demonstrations. In her most-cited paper, "Investigating the Impact of Experience on a User's Ability to Perform Hierarchical Abstraction" (2023, 7 citations), Yang explores how a user’s prior experience influences their capacity to decompose tasks into reusable subtasks—a key step toward making robot learning more intuitive and accessible. This work contributes to bridging the gap between human cognitive strategies and robot learning algorithms, with implications for assistive robotics and industrial automation. Though early in her career, Yang’s research is gaining traction for its focus on user-centered design in robotics, highlighting the importance of human factors in developing effective LfD systems. Her findings offer valuable insights for researchers aiming to democratize robot programming and improve human-robot collaboration in real-world settings.
Research Focus
Key Achievements
Top Papers
- 1