Xiangjun Ji

Papers

Total Citations

H-Index

About

Xiangjun Ji is a leading researcher in medical robotics and intelligent control systems, with a primary focus on advancing safety and precision in surgical applications. His work centers on the critical intersection of adaptive force control, neural network-based tracking, and teleoperation for minimally invasive procedures. Ji’s most cited paper, "Output-Bounded and RBFNN-Based Position Tracking and Adaptive Force Control for Security Tele-Surgery" (2020, 17 citations), addresses a fundamental challenge in e-health brain neurosurgery: enabling surgeons to precisely maneuver an electrocoagulation tool within an extremely narrow cranial workspace. By integrating radial basis function neural networks (RBFNN) with output-bounded control, he developed a framework that ensures both stable position tracking and adaptive force regulation, significantly enhancing operational safety during delicate tissue excavation. This contribution is pivotal for tele-surgery security, directly improving the surgeon’s ability to perform complex tasks remotely without compromising patient safety. Ji’s research is characterized by its practical impact on surgical robotics, offering robust solutions that bridge theoretical control engineering with real-world clinical constraints. His work continues to influence the development of intelligent, adaptive systems for high-stakes medical environments, making him a notable figure in the field of secure and precise robotic-assisted surgery.