Cheng-En Shiue
Papers
1
Total Citations
1
H-Index
1
About
Cheng-En Shiue is a researcher at the forefront of human–robot interaction, specializing in real-time pose recognition and proactive robotic systems. His most notable contribution, "Integrating OpenPose for Proactive Human–Robot Interaction Through Upper-Body Pose Recognition" (2025), introduces a groundbreaking framework that leverages OpenPose’s skeleton estimation to enable tabletop robots to autonomously detect and approach humans based on upper-body gestures. This work bridges computer vision and robotics, allowing machines to initiate natural, context-aware interactions without explicit commands—a critical step toward intuitive social robotics. While his citation count is currently modest (1 citation), the novelty of his approach has positioned him as an emerging voice in the field, with potential applications in assistive technology, collaborative manufacturing, and service robotics. Shiue’s research emphasizes real-time adaptability and human-centric design, addressing key challenges in non-verbal communication between humans and machines. His work is particularly relevant for students and researchers exploring the intersection of deep learning, skeleton tracking, and autonomous systems, offering a practical blueprint for building more responsive and socially aware robots.
Research Focus
Key Achievements
Top Papers
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