Xiaobo Qu received his B.S. and Ph.D. degrees in communication engineering from Xiamen University, P.R. China, in 2006 and 2011, respectively. From 2009 to 2011, he was Visiting Scholar in the Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign. In 2014, he was Visiting Scientist at the Swedish NMR Centre, University of Gothenburg, Sweden. From 2018 to 2019, he was Visiting Scholar in the Department of Radiology, University of Washington at Seattle. Since 2012, he has been a faculty member of Xiamen University, where he is currently Professor in the Department of Electronic Science, leading the computational sensing lab (http://csrc.xmu.edu.cn). He is also affiliated with the Research Center of Magnetic Resonance and Medical Imaging, the National Institute for Data Science in Health and Medicine, and the Research Center for Molecular Imaging and Translational Medicine. He has published a series of papers in prime journals in the fields of medical imaging, biomedical engineering, and signal processing, such as IEEE Trans. Medical Imaging, IEEE Trans. Signal Processing, IEEE Trans. Biomedical Engineering, Medical Image Analysis, Angewandte Chemie International Edition, etc. His research interests include magnetic resonance spectroscopy and imaging, computational imaging, machine learning, and artificial intelligence.
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Alexander Wong, P.Eng., is currently the Canada Research Chair in Artificial Intelligence and Medical Imaging, Member of the College of the Royal Society of Canada, co-director of the Vision and Image Processing Research Group, an associate professor in the Department of Systems Design Engineering at the University of Waterloo, and Co-founder and Chief Scientist of DarwinAI. He has published over 570 refereed journal and conference papers, as well as patents, in various fields such as computational imaging, artificial intelligence, machine learning, and computer vision. In the area of computational imaging, his focus is on integrative computational imaging systems for biomedical imaging (inventor/co-inventor of Correlated Diffusion Imaging, Compensated Magnetic Resonance Imaging, Spectral Light-field Fusion Micro-tomography, Compensated Ultrasound Imaging, Coded Hemodynamic Imaging, High-throughput Computational Slits, Spectral Demultiplexing Imaging, and Parallel Epi-Spectropolarimetric Imaging). In the area of artificial intelligence, his focus is on operational artificial intelligence (co-inventor/inventor of Generative Synthesis, evolutionary deep intelligence, Deep Bayesian Residual Transform, Discovery Radiomics, and random deep intelligence via deep-structured fully-connected graphical models). He has received numerous awards for his research, teaching, and industrial contributions.
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