Won Hee Lee
Papers
2
Total Citations
56
H-Index
2
About
Won Hee Lee is a leading researcher at the intersection of robotics, artificial intelligence, and human-machine interaction. His primary research areas include wearable exoskeleton robots, dexterous manipulation, and deep learning for real-time control systems. Dr. Lee’s major contributions are twofold: first, he developed a groundbreaking real-time human activity recognition system that integrates IMU and encoder sensors with deep learning networks, enabling wearable exoskeletons to intelligently adapt their assistance to users’ daily tasks. This work, published in 2022, has already garnered 52 citations, reflecting its immediate impact on assistive robotics. Second, he pioneered a novel approach to dexterous object manipulation using an anthropomorphic robot hand, combining a natural hand pose transformer with deep reinforcement learning. This research, also from 2022, addresses critical challenges in healthcare, smart homes, and smart factories by enabling robots to perform complex, human-like manipulations. Dr. Lee’s work is notable for bridging the gap between theoretical AI and practical robotic applications, with his activity recognition system being particularly influential in advancing real-time, adaptive control for assistive devices. His contributions are shaping the future of intuitive and responsive robotic systems.
Research Focus
Key Achievements
Top Papers
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