Jun Hyuk Lee

Sungkyunkwan University, Keimyung University

Papers

4

Total Citations

49

H-Index

4

About

Jun Hyuk Lee is a leading researcher in legged robotics and rehabilitation engineering, whose work bridges the gap between dynamic whole-body control and clinical applications. His primary research areas include quadrupedal locomotion, whole-body control, and robot-assisted gait training for stroke rehabilitation. Lee’s major contributions center on developing novel frameworks for stable stair climbing and balance recovery in quadrupedal robots, where he pioneered the use of torque feedback and angular momentum regulation to prevent falls and ensure robust force interaction with complex terrains. His most-cited paper, “Whole-Body Motion and Landing Force Control for Quadrupedal Stair Climbing” (2019, 17 citations), established a foundational approach for minimizing angular momentum changes during climbing. Complementing this, his 2025 systematic review and meta-analysis (14 citations) on robot-assisted gait training in stroke rehabilitation critically evaluated the additive benefits of combining robotic therapy with conventional methods, offering evidence-based guidance for clinical practice. With additional works on torque-sensor-based control and balance recovery, Lee’s research has garnered over 49 citations, demonstrating significant impact in both robotics and rehabilitation communities. His interdisciplinary approach—integrating rigorous control theory with practical rehabilitation outcomes—positions him as a key figure advancing autonomous legged systems and human-centered robotic therapy.

Research Focus

Key Achievements

4
H-Index
4
Papers
49
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
Whole-Body Motion and Landing Force Control for Quadrupedal Stair Climbing
17 citations · 2019
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Sungkyunkwan University, Keimyung University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago