Armaan Kaur Bajwa
Papers
1
Total Citations
19
H-Index
1
About
Armaan Kaur Bajwa’s research lies at the intersection of surgical robotics, human-machine interaction, and medical training, with a focus on improving how surgeons acquire complex technical skills. Her most cited work, “Play Me Back: A Unified Training Platform for Robotic and Laparoscopic Surgery” (2018, 19 citations), introduces a novel training framework that blends hand-over-hand guidance with trial-and-error learning, leveraging expert data captured from the da Vinci surgical system. This approach provides a unified, data-driven platform for both robotic and standard laparoscopic training, addressing a critical gap in surgical education by enabling trainees to learn from expert performance in a structured, repeatable manner. Bajwa’s contributions are particularly notable for their practical impact—her work directly informs the design of more effective, scalable training curricula for minimally invasive surgery. With a growing citation footprint, her research is increasingly recognized for bridging engineering and clinical practice, offering tangible solutions to enhance surgical skill acquisition and patient safety.
Research Focus
Key Achievements
Top Papers
- 1