Papers
3
Total Citations
42
H-Index
3
About
Jian Shi is a leading researcher at the intersection of surgical robotics and intelligent manufacturing, with a primary focus on advancing robotic systems for minimally invasive neurosurgery and precision machining. His most impactful work addresses the critical challenge of intracerebral hemorrhage (ICH)—a devastating stroke subtype with high mortality—through the development of robot-assisted neurosurgical techniques. In his highly cited 2023 review, Shi systematically analyzed the state of the art in surgical robotics for ICH treatment, highlighting how robotic systems can overcome the limitations of conventional minimally invasive surgery, offering greater precision and improved patient outcomes. This work has garnered 29 citations and established him as a key voice in the field. Beyond the operating room, Shi has pioneered innovative approaches to robotic drilling, developing incremental transfer learning methods and end-to-end inclination state monitoring systems using ResNet neural networks. These contributions address the critical challenge of low rigidity in collaborative robots, enabling more reliable and accurate drilling under complex working conditions. His 2024 papers, with 7 and 6 citations respectively, demonstrate his ability to translate deep learning techniques into practical solutions for industrial robotics, marking him as a versatile engineer whose work spans both life-saving medical applications and advanced manufacturing.
Research Focus
Key Achievements
Top Papers
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