Yunyi Zhao
Yunyi Zhao 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). His project is focused on real-time fNIRS motion artifacts processing on edge device. He received his MRes degrees from Imperial College London and BEng degrees from both University of Liverpool (UK) and Xi'an Jiaotong-Liverpool University (China).
Research Interests
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Advanced FPGA Development and Acceleration for Real-Time Neural Network Processing
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Heterogeneous Computing Paradigms in Multi-Processor Systems
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Deep Learning solutions for fNIRS Motion Artifact Processing
Publications
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Zhao, Y. et al., Learning based motion artefacts processing in fNIRS: A mini review. Frontiers in Neuroscience, 2023
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Ercan, R., Xia, Y., Zhao, Y., et al., An Ultra-low-power Real-time Machine Learning based fNIRS Motion Artefacts Detection. Transactions on Very Large Scale Integration Systems, 2023
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Zhao, Y. et al., New Open Source Edge Acceleration SYCL Libraries for Motion Artifact Detection in fNIRS Data. Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, SPIE Photonics West, 2023
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Zhao, Y. et al., FPL Demo: A Learning-Based Motion Artefact Detector for Heterogeneous Platforms. Field Programmable Logic and Applications, 2023
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Zhao, Y. et al., Edge Acceleration for Machine Learning based Motion Artifact Detection on fNIRS Dataset. International Workshop on OpenCL, 2023