Papers

9

Total Citations

101

H-Index

6

About

Suren Kumar’s research lies at the intersection of computer vision, robotics, and healthcare, with a focus on human pose estimation, surgical robotics, and rehabilitation automation. His major contributions include developing methods for estimating human dynamics from monocular video—a challenging problem for articulated systems—and creating computer-vision-based decision support systems to enhance safety in laparoscopic robotic surgery. Kumar also pioneered automation for individualized Kinect-based rehabilitation regimens, bringing quantitative measurement to clinical motor therapy. His work on spatiotemporal articulated models for dynamic SLAM and surgical tool pose estimation from endoscopic video has advanced both robotic perception and surgical skill assessment. With over 100 citations across his most-cited papers, including foundational work in Robotics: Science and Systems (2012) and IEEE publications on surgical performance assessment, Kumar’s impact is evident in enabling safer, more data-driven surgical workflows and accessible rehabilitation technology. His notable achievements include bridging the gap between uncalibrated visual input and real-time pose tracking, directly addressing real-world uncertainties in teleoperated systems.

Research Focus

Key Achievements

6
H-Index
9
Papers
101
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Robotics: Science and Systems VIII
24 citations · 2012
📈 Most Prolific Year: 2015 (3 Papers)
🤝 Key Collaborators: 16
🏛 Institutions: University at Buffalo, State University of New York

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago