Papers
62
Total Citations
1,449
H-Index
19
About
Yunyi Jia is a prominent researcher specializing in human-robot collaboration (HRC), robot learning, and intelligent manufacturing. His work sits at the intersection of robotics, machine learning, and human-centered design, with a particular focus on enabling robots to work seamlessly and safely alongside human partners in real-world manufacturing environments. Jia's most significant contributions include developing the Teaching-Learning-Collaboration (TLC) framework, which allows collaborative robots to learn directly from human demonstrations and assist in complex assembly tasks — a paper that has garnered over 160 citations since 2018. His research has substantially advanced object hand-over control and human intention prediction in shared workspaces, with multiple papers exceeding 80–100 citations. Notably, he has also pioneered natural language-based robot instruction, exploring how robots can acquire new skills through dialogue and verbal guidance, reflecting an early and sustained interest in intuitive human-robot communication. Beyond task execution, Jia has made meaningful contributions to understanding human comfort in HRC environments, authoring influential review papers that help shape safety and ergonomic standards for collaborative robot deployment. His work on deformable object manipulation further broadens the practical scope of robotic automation. With a cumulative citation impact surpassing 800 across his top works, Jia's research continues to define foundational directions in intelligent, human-aware robotics.
Research Focus
Key Achievements
Top Papers
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- 7Teaching Robots New Actions through Natural Language Instructions77 citations · 2014
- 8Learning and Comfort in Human–Robot Interaction: A Review69 citations · 2019
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- 10Human Intention Prediction in Human-Robot Collaborative Tasks57 citations · 2018