Karen Yang
Papers
1
Total Citations
80
H-Index
1
About
Dr. Karen Yang is a leading researcher in robot learning and human-robot interaction, with a focus on bridging natural language and robotic manipulation. Her most-cited work, "Concept2Robot" (2021, 80 citations), introduces a groundbreaking framework that enables robots to learn manipulation concepts directly from human instructions and demonstrations. This work allows robots to map natural language commands to motor skills, learning a single multi-task policy that interprets both linguistic input and visual scenes to generate motion trajectories. Dr. Yang's contributions are pivotal in making robots more intuitive and accessible, reducing the need for explicit programming. Her research has significant implications for assistive robotics, manufacturing, and household automation, where seamless human-robot collaboration is essential. By integrating language understanding with motor control, she addresses a core challenge in embodied AI. With her innovative approach and growing citation impact, Dr. Yang is shaping the future of intelligent, interactive robotic systems that can learn from and adapt to human guidance.
Research Focus
Key Achievements
Top Papers
- 1