Suokui Chang
Papers
1
Total Citations
24
H-Index
1
About
Dr. Suokui Chang is a leading researcher in the field of human-robot interaction, with a primary focus on intention recognition and collaborative robotics. His most impactful work, "Human-Robot Collaboration by Intention Recognition using Deep LSTM Neural Network" (2019, 24 citations), introduces a novel framework that enables robots to interpret human motion sequences in real time, significantly enhancing the fluidity and safety of collaborative tasks. By leveraging deep LSTM neural networks to analyze skeleton-based motion data, Dr. Chang’s approach allows robots to anticipate human actions rather than merely react, marking a critical advancement in assistive and industrial robotics. This work has been widely cited for its practical implications in manufacturing and service robotics, where seamless human-robot teamwork is essential. Dr. Chang’s contributions continue to shape the development of more intuitive and responsive robotic systems, bridging the gap between human intent and machine action.
Research Focus
Key Achievements
Top Papers
- 1