Papers
4
Total Citations
9
H-Index
2
About
Christian Kunz is a researcher at the forefront of surgical robotics and augmented reality for medicine. His work focuses on making minimally invasive and neurosurgical interventions safer, more intuitive, and increasingly autonomous. Kunz’s key contributions span three critical areas: risk-aware surgical planning, intuitive robot control, and scene understanding for automation. His most cited work, "Multimodal Risk-Based Path Planning for Neurosurgical Interventions" (2021, 4 citations), introduces a planning tool that optimizes surgical trajectories to minimize damage to vital brain structures. He has also advanced human-robot collaboration with "Augmented Reality-based Robot Control for Laparoscopic Surgery" (2022, 2 citations), enabling surgeons to guide robots more naturally. To address the bottleneck of manual data annotation, Kunz developed LapSeg3D (2022, 2 citations), a deep neural network for weakly supervised semantic segmentation of surgical point clouds. His latest work, "Semi-Autonomous Robotic Assistance for Gallbladder Retraction" (2025, 1 citation), tackles the challenge of deploying robots in unpredictable surgical environments. Through these innovations, Kunz is paving the way for a future where robots act as intelligent, semi-autonomous partners in the operating room.
Research Focus
Key Achievements
Top Papers
- 1Multimodal Risk-Based Path Planning for Neurosurgical Interventions4 citations · 2021
- 2Augmented Reality-based Robot Control for Laparoscopic Surgery2 citations · 2022
- 3
- 4Semi-Autonomous Robotic Assistance for Gallbladder Retraction in Surgery1 citations · 2025