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About

Shiou-Yun Jeng is a researcher specializing in intelligent control systems, mobile robotics, and computational intelligence, with a particular focus on integrating fuzzy logic, neural networks, and evolutionary optimization algorithms to solve complex real-world control problems. Jeng's most impactful contributions center on autonomous mobile robot navigation, where innovative hybrid frameworks — such as the fuzzy logic controller with reinforcement-enhanced differential search (FLC_R-IDS) and knowledge-based neural fuzzy controllers optimized through cultural multi-strategy differential evolution — have demonstrated superior performance in wall-following and obstacle avoidance tasks. These foundational works have collectively garnered over 40 citations, reflecting their meaningful influence within the robotics and computational intelligence communities. Jeng has also made notable advances in uncertainty-robust modeling through interval type-2 fuzzy neural networks optimized via improved particle swarm optimization, offering enhanced noise suppression over traditional type-1 architectures. Extending beyond mobile robotics, Jeng's research has explored voice-based mechanical arm control using improved keyword extraction techniques, signaling a forward-looking interest in human-robot interaction. Overall, Jeng's body of work represents a cohesive effort to bridge intelligent computational methods with practical autonomous systems engineering.