Ing-Jr Ding
Papers
8
Total Citations
191
H-Index
6
About
Ing-Jr Ding is a leading researcher in human–robot interaction (HRI) and assistive robotics, with a focus on gesture and speech recognition for intelligent robotic control. His work centers on developing natural, non-invasive interfaces—using depth sensors like Kinect and wearable devices such as the Myo armband—to enable robots to interpret human commands via hand gestures, voice, and biometric signals. Ding’s most cited paper (42 citations) demonstrates a Kinect microphone array for speech and speaker recognition to control humanoid robots in exhibition settings. He has also pioneered adaptive hidden Markov model (HMM)-based gesture recognition to simplify large-scale video data processing for robot imitation learning. His contributions extend to assistive technology, notably a service robot system integrating a wearable Myo armband for specialized hand gesture interfaces, empowering people with mobility disabilities. With over 190 total citations across his top works, Ding’s research has significantly advanced smart manufacturing, material-handling robots, and autonomous guided vehicles (AGVs) using ROS-based SLAM navigation. His innovative HCI schemes—combining surface electromyography and inertial measurement units—represent a major step toward inclusive, gesture-driven robotic assistance.
Research Focus
Key Achievements
Top Papers
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