Yunjia Xia
Yunjia Xia is a PhD student at HUB of Intelligent Neuro-Engineering (HUBIN) of the Division of Surgery and Interventional Science at the University College London (UCL). He is also a member of DOT-HUB at the UCL. His project is mainly focused on AI-supported wearable brain imaging and brain computer interface. Prior to his PhD study, he received his MRes and BEng degrees from the UCL-University of Cambridge, United Kingdom, and Beihang University, China, respectively.
Research Interests
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FPGA Development and Application in Wearable and Interventional Medical Technologies
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AI Hardware Optimization for Enhanced Functional Brain Imaging
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Brain-Computer Interface (BCI) for Rehabilitation and Healthcare Monitoring
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Advanced Electronics Integration in Medical Devices for Improved Healthcare Solutions
Publications
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Xia, Y. et al. (2023). A low-cost, smartphone-based instant 3D scanning system for infant fNIRS applications. Neurophotonics, 10(4):046601.
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Chen, J., Xia, Y. et al. (2023). fNIRS-EEG brain computer interface for rehabilitation. Bioeigneering, 10(12).
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Zhou, X., Xia, Y. et al. (2023). Review of recent advances in frequency-domain near-infrared spectroscopy technologies. Biomedical Optics Express, 14(7), 3234-3258.
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Xia, Y. et al. (2023). A remote-control, smartphone-based automatic 3D scanning system for fNIRS/DOT applications. Optica Biophotonics Congress: Optics in the Life Sciences.
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Zhao, Y., Xia, Y., et al. (2023). Edge acceleration for machine learning-based motion artifact detection on fNIRS dataset. The 11th IWOCL.
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Renas Ercan, Y. Xia, Y. Zhao, R. Loureiro, S. Yang, and H. Zhao, “An Ultralow-Power Real-Time Machine Learning Based fNIRS Motion Artifacts Detection,” pp. 1–11, Jan. 2024, doi: https://doi.org/10.1109/tvlsi.2024.3356161.