Sirisha Rambhatla

University of Southern California

Papers

1

Total Citations

14

H-Index

1

About

Sirisha Rambhatla is a researcher at the forefront of advancing surgical robotics through artificial intelligence, with a primary focus on automating skill assessment in robotic suturing. Her work addresses a critical bottleneck in surgical training: the mislabeling of ground truth data, which can skew the evaluation of trainee performance. In her highly cited 2021 paper, "Road to automating robotic suturing skills assessment: Battling mislabeling of the ground truth," she proposes robust methods to correct these inaccuracies, ensuring that AI-driven assessments are both reliable and clinically meaningful. This contribution has garnered 14 citations, reflecting its impact on the field of computer-assisted surgery. By tackling data quality challenges, Rambhatla’s research paves the way for more objective, scalable, and precise training tools, ultimately aiming to enhance patient safety and surgical outcomes. Her work stands as a key step toward integrating AI into the operating room, making her a notable voice in the intersection of robotics, machine learning, and medical education.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Road to automating robotic suturing skills assessment: Battling mislabeling of the ground truth
14 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Southern California

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago