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About

Martin Kibsgaard is a researcher focused on advancing surgical training through simulation and augmented reality, particularly for robot-assisted minimally invasive surgery. His work addresses critical barriers in surgical education—namely, the high cost and limited accessibility of training systems. Kibsgaard’s most cited paper, “Depth cues in augmented reality for training of robot-assisted minimally invasive surgery” (2017, 12 citations), explores how AR can enhance instructor-trainee communication by overlaying virtual surgical cues onto real-time video streams. He also pioneered low-cost simulation approaches, as seen in “Low-cost simulation of robotic surgery” (2013, 7 citations), which aims to reduce the financial burden of training on expensive robotic equipment. His innovative use of game engines for simulating surgical cutting in deformable bodies (2014, 5 citations) further democratizes access to realistic training tools. Additionally, Kibsgaard’s work on measuring latency in AR systems (2017, 5 citations) ensures that these technologies maintain the precision required for teleoperation. By combining affordability, realism, and interactivity, Kibsgaard’s contributions are paving the way for more accessible and effective surgical training, ultimately improving patient outcomes.