Shijin Zhang

Yangtze River Delta Physics Research Center (China), Chinese Academy of Sciences, Shanghai University

Papers

Total Citations

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About

Shijin Zhang is a researcher whose work bridges the frontiers of intelligent robotics, brain-computer interfaces (BCIs), and autonomous vehicle localization. His primary research areas include noninvasive EEG-based robotic control, dead reckoning calibration for self-driving vehicles, and advanced manufacturing path generation. Zhang’s major contributions are twofold: first, he has advanced the practical deployment of BCIs by reviewing the latest noninvasive EEG-driven devices—such as robotic exoskeletons and wheelchairs—that assist both disabled users and able-bodied individuals, with his 2022 review garnering 6 citations. Second, he developed a novel dead reckoning calibration scheme using an adaptive quantum-inspired evolutionary algorithm, which optimizes vehicle self-localization without requiring specially designed paths—a key step toward robust autonomous driving. His work on generating abrasive waterjet cutting paths for large, poorly-defined parts further demonstrates his versatility in solving real-world manufacturing challenges. With a growing citation impact, Zhang’s research is notable for its focus on practical, scalable solutions that push the boundaries of intelligent systems, from assistive robotics to autonomous navigation.