Julien Quarez
Papers
3
Total Citations
5
H-Index
2
About
Julien Quarez is a leading researcher at the intersection of embodied AI and surgical robotics, with a focus on transforming the operating room through intelligent data systems and skill assessment. His most impactful work introduces MUTUAL, a pioneering cross-platform multimodal data recording and streaming software designed to support the development and deployment of intelligent surgical agents. Successfully deployed in two clinical studies, MUTUAL enables holistic sensing and real-time inference, laying the groundwork for next-generation robotic surgery. Quarez has also made significant contributions to surgical skill evaluation, developing the Recursive Cross Attention Network (ReCAP) for pseudo-label generation, which enhances automated skill assessment using established OSATS and GRS metrics. Additionally, his comparative analysis of left- and right-hand workspaces in robotic training has practical implications for optimizing surgeon ergonomics and learning. With his papers already accumulating citations in the competitive field of surgical AI, Quarez is establishing himself as a key innovator in creating the data infrastructure and analytical tools needed to advance robotic surgery from research to routine clinical practice.
Research Focus
Key Achievements
Top Papers
- 1MUTUAL: Towards Holistic Sensing and Inference in the Operating Room2 citations · 2025
- 2
- 3