Boxing Su
Papers
1
Total Citations
2
H-Index
1
About
Boxing Su is a rising researcher at the intersection of medical robotics and surgical optimization, with a primary focus on improving minimally invasive urological procedures. His most notable contribution lies in the development of advanced puncture path planning algorithms for flexible needles used in percutaneous nephrolithotomy (PCNL), a critical treatment for large kidney stones. In his 2025 paper, Su introduced a hybrid NSGA optimizer that addresses the challenge of establishing precise, safe puncture trajectories—a task that traditionally demands extensive surgical expertise. This work, already garnering 2 citations in its early publication stage, demonstrates his ability to combine multi-objective optimization with practical clinical needs. By automating path planning, Su’s research aims to reduce surgeon training requirements and enhance procedural safety, potentially transforming how complex kidney stone surgeries are performed. His work represents a meaningful step toward integrating artificial intelligence into surgical navigation, positioning him as an emerging voice in the field of computer-assisted intervention.
Research Focus
Key Achievements
Top Papers
- 1