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About

Dongcen Xu is a pioneering researcher at the intersection of brain-computer interfaces (BCI) and robotics, whose work is reshaping how humans interact with machines. His primary research areas span SSVEP-based BCI systems, deep learning for EEG signal processing, and semi-autonomous robotic control. Xu’s most impactful contribution is his comprehensive survey on deep learning models in SSVEP-based BCI (48 citations), which has become a foundational reference for researchers developing non-invasive neural interfaces. He further advanced the field with FB-CCNN, a novel filter bank complex spectrum convolutional neural network that achieves superior EEG classification through artificial gradient descent optimization. In robotics, Xu developed a semi-autonomous BCI-controlled robotic system capable of executing grasping tasks, demonstrating practical applications for assistive technology. His work on hand-eye calibration using stereo cameras offers a fast, straightforward solution for robotic perception, while his design of a reconfigurable tracked mobile deep-sea rover (R-ROV) showcases his versatility in tackling complex engineering challenges. With a growing citation impact and innovations spanning from neural decoding to underwater robotics, Xu is establishing himself as a versatile engineer whose work bridges cognitive neuroscience and autonomous systems, promising transformative applications in rehabilitation and human-robot collaboration.