Qingyang Hong

Xiamen University, City University of Hong Kong

Papers

Total Citations

H-Index

About

Qingyang Hong is a researcher whose work bridges robotics, artificial intelligence, and human-computer interaction, with a particular focus on intelligent systems and speech recognition. Their key research areas include dynamic path planning for mobile robots, embedded speech recognition, and EEG-based communication systems. Hong’s major contributions include pioneering the use of fuzzy-neural networks for real-time obstacle avoidance and route optimization in robotics, as demonstrated in their most-cited paper (17 citations), which offers a robust alternative to traditional path planning methods. They also advanced embedded systems by developing a speaker-independent speech recognition system for intelligent robots, overcoming computational and memory constraints (8 citations). Additionally, Hong explored brain-computer interfaces through EEG-based Chinese spelling systems (3 citations), contributing to assistive technology. Their work has practical implications for autonomous navigation, voice-controlled robotics, and accessibility tools, with cumulative citations reflecting steady impact in niche but critical domains. Hong’s achievements highlight a commitment to integrating neural networks and fuzzy logic into real-world applications, making their research valuable for students and engineers in robotics, AI, and embedded systems.