Kelong Chen
Papers
1
Total Citations
4
H-Index
1
About
Kelong Chen is a pioneering researcher in the field of medical robotics and intelligent surgical systems, with a focus on advancing autonomous and semi-autonomous neurosurgical procedures. His work centers on developing novel path planning algorithms for craniotomy surgical robots, where he has made significant contributions to improving the safety, precision, and efficiency of preoperative planning. Chen’s most notable contribution is the improved MDP-LQR-RRT* algorithm, which integrates Markov decision processes with linear-quadratic regulators and rapidly exploring random trees to generate optimal, collision-free trajectories for robotic craniotomies. This work, published in 2025 and already garnering 4 citations, demonstrates his ability to bridge theoretical control theory with practical surgical applications. By addressing the critical challenge of real-time path optimization in constrained anatomical environments, Chen’s research has the potential to reduce human error and shorten operation times in complex cranial surgeries. His achievements highlight a commitment to translating robotics and AI innovations into clinical tools, positioning him as a rising figure in the intersection of robotics, control systems, and neurosurgery.
Research Focus
Key Achievements
Top Papers
- 1