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I achieved a M.Sc. in Biomedical Engineering from China Medical University and a Ph.D. in Electrical Engineering from Otto-von-Guericke University. Currently, I am an instructor at Harvard Medical School as well as research associate at the department of newborn medicine, Boston Children’s Hospital . My work focuses on developing new types of data analysis software to improve the utility of BabyMEG and applying these methods for brain activity analysis in healthy children and children with various types of brain disorder. I was a Research Fellow in the Department of Radiology at Harvard Medical School’s General Hospital. Before that I had post-doc training at the Max Planck Institute for Brain Research at Frankfurt am Main, Germany.

My main research interests are the artificial signals removal during the biomedical signal recording, the development of MEG acquisition system, embedded coding, and the psychology analysis on Autism Spectrum Disorders (ASD) and schizophrenia. My past key contributions are the introduction of Maximum Noise Fraction algorithm in the EEG/fMRI signal artifacts removal, the development of a motion adjustment moving averaging subtraction method for removing the gradient artifacts during EEG/fMRI recording, and the investigation of abnormal neural oscillations in cognition and perception in ASD and schizophrenia. Currently, the most important contribution is the development of a completely new babyMEG acquisition system.

My other research interest is related to deep learning. I used the deep neural network for the applications of the noise cancellation and cancer classification