J. Classe
Papers
1
Total Citations
37
H-Index
1
About
J. Classe is a pioneering researcher in the field of human-robot interaction, with a particular focus on the sociotechnical dynamics of robotic surgery. Their work critically examines how experience and workplace culture shape team performance in high-stakes medical environments, bridging the gap between engineering, psychology, and surgical practice. Classe’s most-cited paper, a 2012 case study on human-robot team interaction in robotic surgery, has garnered 37 citations, establishing a foundational framework for understanding how non-technical factors—such as communication, trust, and organizational norms—influence surgical outcomes. This research has been instrumental in moving the conversation beyond purely technical metrics, highlighting the need for training protocols that account for team dynamics and cultural context. By integrating qualitative insights with quantitative performance data, Classe has contributed to safer, more effective robotic surgery systems. Their work is essential reading for students and researchers interested in the human side of automation, offering a nuanced perspective on how experience and culture can make or break the success of human-robot teams in critical care settings.
Research Focus
Key Achievements
Top Papers
- 1