Shuying Zhang

University of Minnesota, University of Minnesota System

Papers

Total Citations

H-Index

About

Shuying Zhang is a researcher working at the intersection of neuroscience and assistive robotics, with a primary focus on brain-computer interface (BCI) technologies. Zhang's most notable work centers on developing noninvasive, electroencephalogram (EEG)-based systems that enable direct neural control of robotic devices, representing a significant step forward in translating BCI research from virtual environments to real-world applications. Most prominently, Zhang contributed to pioneering research demonstrating that EEG signals could be harnessed to control a robotic arm for complex reach and grasp tasks — a meaningful advancement over earlier work limited to controlling computer cursors, virtual helicopters, or simpler mobility devices like wheelchairs. This research holds profound implications for individuals with motor impairments, potentially offering greater independence and rehabilitation opportunities. Zhang's work has garnered citations across multiple publications, including a formal author correction that underscores the scholarly rigor applied to ensuring research accuracy and integrity. While still building a citation profile, Zhang's contributions represent an important bridge between fundamental neuroscience and practical assistive technology, making their work particularly relevant to students and researchers exploring neuroprosthetics, rehabilitation engineering, and human-machine interaction.