Papers
2
Total Citations
4
H-Index
2
About
Yong-Li Yan is a rising researcher in the field of robotic surgery and teleoperation systems, with a focus on enhancing safety and precision in minimally invasive procedures. His key research areas include force prediction, nonlinear control, and flexible joint manipulation. Yan’s major contribution lies in developing robust computational models to address critical challenges in robot-assisted surgery. His most cited work introduces an improved sparrow search algorithm (ISSA) optimized backpropagation neural network to predict tool-tissue interaction forces, a solution aimed at preventing soft tissue damage caused by excessive clamp force during minimally invasive surgery. Additionally, his research on nonlinear extended state observer-based control for teleoperation systems tackles the complexities of flexible joint uncertainties, improving pose control and synchronization in remote surgical scenarios. Though early in his career—with each of his top papers garnering 2 citations—Yan’s work demonstrates significant potential for real-world impact, offering innovative approaches to enhance surgical safety, efficiency, and operational reliability in robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2