Joyce Duan

Papers

Total Citations

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About

Joyce Duan is a rising voice in human-robot interaction, best known for her pioneering work on reciprocal human-robot learning. Her most-cited paper, "Why We Should Build Robots That Both Teach and Learn" (2021, 7 citations), introduces a transformative framework where robots are not merely passive learners but active educators. Duan proposes a methodology for robots to acquire a skill from an expert, perform it independently or collaboratively, and then teach that skill to a novice—closing the loop in human-robot skill transfer. This work challenges conventional one-directional learning models, positioning robots as partners in a bidirectional teaching-learning cycle. While still early in her career, Duan’s contributions are already shaping discussions on adaptive robotics and collaborative AI. Her research has implications for education, rehabilitation, and manufacturing, where robots can both learn from humans and instruct them. By redefining the robot’s role from tool to co-educator, Duan is laying the groundwork for more intuitive, socially integrated robotic systems. Her work signals a future where machines not only acquire knowledge but also empower human growth.