Seung-kook Jun

University at Buffalo, State University of New York

Papers

8

Total Citations

116

H-Index

6

About

Seung-kook Jun is a robotics and biomedical engineering researcher whose work bridges two compelling domains: cable-driven robotic systems and computer-assisted surgical training. His most influential contributions have emerged from the intersection of automation, motion analysis, and healthcare technology, garnering over 100 cumulative citations across his published work. Jun's robotics research has significantly advanced the field of mobile cable robots, exploring how configuration redundancy and reconfigurable attachment points can be exploited to modulate stiffness and optimize tension distribution in planar systems. His 2014 paper on stiffness modulation via elastic cables demonstrated elegant solutions for tension control without relying on force sensors, opening new design pathways for flexible robotic platforms. Equally impactful is Jun's pioneering work in surgical skill assessment, where he developed automated, video-analysis-based motion studies to bring quantitative rigor to the traditionally subjective evaluation of robotic minimally invasive surgical performance. His most-cited paper in this area has accumulated 35 citations and helped lay the groundwork for objective, repeatable performance metrics in surgical training. Complementing this, his work on Kinect-based exercise individualization reflects a broader commitment to data-driven, cyber-physical approaches in clinical rehabilitation and smart health systems.

Research Focus

Key Achievements

6
H-Index
8
Papers
116
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
Robotic Minimally Invasive Surgical skill assessment based on automated video-analysis motion studies
35 citations · 2012
📈 Most Prolific Year: 2013 (4 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University at Buffalo, State University of New York

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago