Parisa Hasani
Papers
1
Total Citations
2
H-Index
1
About
Parisa Hasani is a researcher advancing the field of robotic-assisted minimally invasive surgery (RMIS) through computational approaches to surgical skill assessment. Her work centers on developing automated frameworks that can evaluate surgeon proficiency, particularly in suturing tasks, using kinematic data from robotic systems. This research addresses a critical bottleneck in surgical training: the heavy reliance on expert surgeons for manual feedback. By creating efficient computational models, Hasani aims to streamline the assessment process, enabling novice surgeons to receive objective, real-time evaluations during their residency. Her most-cited paper, "Towards an Efficient Computational Framework for Surgical Skill Assessment: Suturing Task by Kinematic Data" (2021), has garnered 2 citations, reflecting its foundational role in this emerging area. While early in her career, Hasani’s contributions hold significant promise for reducing expert workload and accelerating skill acquisition in RMIS training. Her work sits at the intersection of robotics, machine learning, and medical education, offering a pathway toward more autonomous, data-driven surgical training systems that could ultimately improve patient outcomes and surgical precision.
Research Focus
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Top Papers
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