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Kuo-Yang Wang is a researcher whose work bridges the critical fields of perioperative medicine and intelligent robotics, with a particular focus on mobile robot control and fuzzy logic systems. His most cited paper, "Hypoxemia During One-Lung Ventilation for Robot-Assisted Coronary Artery Bypass Graft Surgery" (2013, 28 citations), demonstrates a significant contribution to anesthesiology, addressing a key challenge in robotic cardiac surgery. In robotics, Wang has pioneered the application of hybrid controllers, notably developing a GA-PSO (Genetic Algorithm-Particle Swarm Optimization) method to optimize fuzzy controllers for robot soccer, determining optimal velocities for dynamic environments. He has also explored fuzzy ant colony optimization for path planning and obstacle avoidance in soccer robots, integrating generalized predictive control for enhanced performance. With a citation count of 49 across his top five papers, Wang’s work is characterized by its interdisciplinary nature—applying advanced computational intelligence to both medical and robotic domains. His achievements include the development of novel hybrid algorithms that improve autonomous decision-making in complex, real-time scenarios, making his research valuable for students and researchers interested in the convergence of AI, control systems, and practical applications in surgery and robotics.