Jihyun Lee
Papers
9
Total Citations
111
H-Index
6
About
Jihyun Lee is a robotics and manufacturing researcher whose work bridges intelligent diagnostics, precision machining, and advanced biofabrication. With a growing body of highly cited publications, Lee has established a strong reputation in applying machine learning and sensor fusion to solve real-world industrial challenges. Among Lee's most influential contributions is the development of an explainable fault diagnosis framework for robotic spot-welding using sensor data imagification, which addresses the critical issue of model transparency in industrial AI systems and has garnered 33 citations since 2021. This commitment to interpretable, reliable automation carries through to work on robotic milling, where Lee has pioneered indirect cutting force measurement via multiple sensors and machine learning (22 citations) and developed nonlinear disturbance observer-based methods to compensate for compliance errors inherent to low-rigidity robotic systems. Lee's research increasingly extends into biomedical manufacturing, with notable work on vision-based tool path compensation for robotic 3D bioprinting (23 citations) and multi-axis printing strategies for complex curved tissue geometries. Across these domains, Lee consistently tackles the gap between theoretical capability and real-world precision — making contributions that are both technically rigorous and practically impactful for the next generation of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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- 7Cable-assisted robotic system (CARS) for machining operations4 citations · 2023
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