Asli Okur
Papers
1
Total Citations
2
H-Index
1
About
Asli Okur is a researcher whose work lies at the intersection of surgical robotics, human-robot interaction, and workflow analysis. Her most cited paper, "Detecting and Analyzing the Surgical Workflow to Aid Human and Robotic Scrub Nurses" (2014), addresses a critical challenge in the operating room: capturing the implicit, experience-based mental models that surgeons and nurses develop for each procedure. By detecting and analyzing surgical workflows, Okur’s research aims to enable both human and robotic scrub nurses to anticipate a surgeon’s next move, thereby improving coordination and efficiency during surgery. This foundational work, which has garnered 2 citations, lays the groundwork for more intuitive and responsive robotic assistants in the operating theater. Okur’s contributions are particularly notable for bridging the gap between cognitive science and robotics, translating tacit human knowledge into actionable data for autonomous systems. Her research holds promise for reducing surgical errors, enhancing teamwork, and ultimately improving patient outcomes, marking her as a forward-thinking contributor to the future of computer-assisted surgery.
Research Focus
Key Achievements
Top Papers
- 1