Alok Mohan Uppar
Papers
1
Total Citations
10
H-Index
1
About
Alok Mohan Uppar is a researcher at the intersection of neurosurgery and artificial intelligence, with a primary focus on automated surgical skill assessment and intra-operative video analysis. His most cited work, "Automated Microsurgical Tool Segmentation and Characterization in Intra-Operative Neurosurgical Videos" (2022, 10 citations), addresses a critical bottleneck in surgical education: the time-intensive, subjective nature of checklist-based skill evaluation. By developing computer vision methods to automatically segment and characterize microsurgical tools in real surgical footage, Uppar offers a scalable, objective alternative that reduces assessor bias and enables routine, data-driven feedback. This contribution is particularly impactful for neurosurgical training, where precision and dexterity are paramount. His research demonstrates how AI can transform surgical pedagogy, moving from expert-dependent assessment to automated, reproducible analysis. With a growing citation footprint, Uppar is establishing himself as a key voice in surgical data science, bridging the gap between clinical practice and machine learning to improve both patient outcomes and the next generation of surgeon training.
Research Focus
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Top Papers
- 1