Ayberk Acar
Papers
4
Total Citations
11
H-Index
2
About
Ayberk Acar is pioneering the integration of cognitive sensing and autonomy into robotic surgery, with a focus on making telerobotic systems more intuitive and capable. His research spans three critical frontiers: cognitive load estimation via pupillometry, monocular 3D scene understanding for autonomous action, and force estimation for haptic feedback. In his highly cited 2023 work, Acar systematically evaluated algorithms for estimating surgeon cognitive effort from pupillometry data during telerobotic procedures, establishing a foundation for gaze-based adaptive interfaces. He followed this by comparing eye tracker designs for cognitive load assessment in tele-robotic surgery, directly addressing the practical challenges of deploying these sensors in clinical settings. Looking toward automation, his 2025 paper on guiding tumor resection through monocular 3D reconstruction proposes a solution to the space constraints of current depth-camera approaches, enabling autonomous surgical guidance with minimal hardware. Additionally, his work on force estimation methods for the da Vinci Research Kit tackles the critical lack of haptic feedback in earlier systems. With growing citations across these interconnected contributions, Acar is shaping a future where surgical robots not only see and feel, but also understand the cognitive state of their human operators.
Research Focus
Key Achievements
Top Papers
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