Ying Tan

University of Melbourne, Beijing Institute of Technology

Papers

Total Citations

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About

Ying Tan is an emerging researcher working at the intersection of assistive robotics, human-machine interfaces, and brain-computer interface (BCI) systems. Their work focuses on advancing the capabilities of powered lower limb exoskeletons for individuals with spinal cord injuries (SCI), as well as developing sophisticated neural signal processing frameworks for BCI applications. Among Tan's notable contributions is their investigation into crutch force sensors as a means of predicting user intent in assistive exoskeletons, a critical step toward enabling these devices to navigate the complex demands of everyday environments. Complementing this, their research into volitional movement exploitation seeks to give exoskeleton users greater autonomy over gait parameters such as step length, directly addressing one of the field's most pressing challenges. Tan has also made strides in neural engineering, proposing a multi-scale EEGNet architecture designed to improve cross-subject classification in rapid serial visual presentation (RSVP)-based BCI systems. Though early in their citation trajectory — with their 2022 publications accumulating up to three citations — Tan's research tackles highly relevant and impactful problems that bridge rehabilitation engineering and neurotechnology, positioning them as a promising voice in assistive technology research.