Xiuze Yang
Papers
2
Total Citations
38
H-Index
2
About
Xiuze Yang is a leading researcher in the fields of surgical robotics, human-robot interaction, and intelligent automation. His work focuses on enhancing the safety, precision, and assessment of robotic systems, particularly in teleoperation and minimally invasive surgery. Yang’s major contributions include developing a collision risk assessment and automatic obstacle avoidance strategy for teleoperation robots, a critical advancement for improving operator safety in complex environments. He also pioneered an automated skill assessment framework that uses visual motion signals and deep neural networks to evaluate surgical instrument tip (SIT) motion, enabling objective, data-driven quantification of surgical performance. This work, published in 2023, has already garnered 12 citations, while his 2022 paper on collision avoidance has received 26 citations, demonstrating growing impact in the robotics community. By integrating motion analysis with machine learning, Yang is helping to standardize surgical training and improve the accuracy of robotic operations. His research bridges the gap between human skill and autonomous assistance, offering practical solutions for next-generation surgical and teleoperated systems.
Research Focus
Key Achievements
Top Papers
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