Yongmei Fan

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About

Yongmei Fan is a researcher at the forefront of brain-computer interface (BCI) technology, with a primary focus on integrating neural signals with robotic systems to assist mobility-impaired individuals. Her most-cited work, "DeepBrain" (2022), has garnered 9 citations and represents a significant step forward in combining electroencephalograph (EEG) techniques with machine learning to enable mind-controlled robotic assistance. This contribution addresses a critical challenge in BCI—translating brain signals into reliable, real-world commands—offering new possibilities for assistive robotics. Fan’s research sits at the intersection of neural engineering, human-robot interaction, and applied artificial intelligence, where she explores how deep learning models can decode EEG patterns with greater accuracy. Her work is notable for its practical orientation, aiming to bridge the gap between laboratory BCI systems and everyday use for people with disabilities. Through "DeepBrain" and related studies, Fan has established herself as an emerging voice in the BCI community, contributing to a future where thought alone can control prosthetic limbs or wheelchairs, restoring independence and quality of life.