JaeWook Shin

Papers

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About

JaeWook Shin is a researcher at the forefront of human–robot interaction (HRI) and intelligent robotic control, with a strong focus on smart factory automation. His most impactful work, "EMG-Based Dynamic Hand Gesture Recognition Using Edge AI for Human–Robot Interaction" (2023, 45 citations), pioneers the use of surface electromyography (sEMG) signals processed via edge artificial intelligence to enable intuitive, real-time hand gesture control of industrial robots. This contribution directly addresses the need for seamless, non-invasive operator interfaces in Industry 4.0 environments. Shin’s earlier research, including "ROS based Embedded System using a Joystick for Industrial Robots Remote Control" (2021), demonstrates his expertise in embedded systems and the Robot Operating System (ROS), developing algorithms for inverse kinematics and coordinate transformation to ensure safe, feasible robot motion. Additionally, his work on underwater acoustics, "Direction and Location Estimating Algorithm for Sound Sources with Two Hydrophones in Underwater Environment" (2013), reveals a broader interest in sensor-based localization for autonomous vehicles. By bridging edge AI, biosignal processing, and robust control architectures, Shin’s research is shaping the next generation of responsive, human-centric robotic systems for both industrial and specialized environments.