Papers
1
Total Citations
45
H-Index
1
About
EunSu Kim is a leading researcher at the intersection of human–robot interaction (HRI) and edge artificial intelligence, with a primary focus on advancing intuitive control systems for smart manufacturing environments. His most notable contribution is the development of an EMG-based dynamic hand gesture recognition system that leverages edge AI to enable real-time, low-latency robot control without relying on cloud computing. This work, published in 2023 and already garnering 45 citations, addresses a critical bottleneck in industrial HRI by allowing workers to command robots through natural hand movements captured via surface electromyography signals. Kim’s approach not only improves operational efficiency in smart factories but also enhances worker safety by reducing physical contact with machinery. His research is distinguished by its practical deployment focus—bridging the gap between laboratory-grade machine learning models and real-world industrial constraints such as limited computational resources and the need for robust, real-time performance. Through this work, Kim has established himself as a key figure in the emerging field of edge AI for wearable robotics, with his findings directly informing the next generation of human-centric automation systems.
Research Focus
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Top Papers
- 1