Reza Askari

Sisters of Charity Hospital, University at Buffalo, State University of New York

Papers

Total Citations

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About

Dr. Reza Askari’s research bridges two distinct frontiers: advanced gynecologic surgery and intelligent robotic navigation. In gynecologic robotic-assisted surgery, Askari has made impactful contributions to optimizing patient outcomes. His most cited work, “Trendelenburg Position in Gynecologic Robotic-Assisted Surgery” (2012, 76 citations), addresses critical intraoperative positioning techniques, while his study on “Use of a bidirectional barbed suture in robot-assisted sacrocolpopexy” (2010, 16 citations) advanced surgical efficiency and tissue approximation. In parallel, Askari has pioneered innovations in service robotics, notably in “Service Robot Navigation Based on Q-Learning and Fuzzy Logic” (2011, 6 citations). This work introduced a novel hybrid approach combining reinforcement learning with fuzzy logic, enabling service robots—such as nurse or reception robots—to navigate semi-structured indoor environments dynamically. By integrating machine learning with classical control, Askari’s research addresses real-world challenges in autonomous mobile robotics. His dual expertise across surgical robotics and autonomous navigation demonstrates a rare interdisciplinary vision, with his surgical work achieving the highest citation impact. Askari’s contributions continue to influence both clinical practice and intelligent robotic systems, marking him as a versatile researcher at the intersection of medicine and engineering.