Stanford University
Postdoctoral Scholars
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Bernard Ng

Academic Appointments

  • Postdoctoral Research fellow, Neurology and Neurological Sciences

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Bio

I currently hold a joint postdoctoral position at the Functional Imaging in Neuropsychiatric Disorders (FIND) lab of Stanford University and the Parietal team of INRIA under the mentorship of Dr. Michael Greicius and Dr. Bertrand Thirion. I was previously a member of the Biomedical Signal and Image Computing Lab (BiSICL) and earned my Ph.D degree in electrical engineering at the University of British Columbia (UBC) under the guidance of Dr. Rafeef Abugharbieh. I obtained my M.A.Sc degree in electrical engineering at UBC under the joint supervision of Dr. Rafeef Abugharbieh and Dr. Martin McKeown and received my B.A.Sc. degree in electronics engineering at Simon Fraser University (SFU) working under Dr. Theodore Milner and Dr. David Franklin.

Professional Education

Doctor of Philosophy: The University of British Columbia, Electrical and Computer Engineering (2011)
Master of Applied Science: The University of British Columbia, Electrical and Computer Engineering (2007)
Bachelor of Applied Science: Simon Fraser University, Electronics Engineering (2005)

Stanford Advisors

Michael Greicius: Postdoctoral Faculty Sponsor

Research & Scholarship

Current Research and Scholarly Interests

My main research interest lies in developing new computational methods that extend concepts from machine learning, optimization, graphical models, and statistics for biomedical applications. I am currently devising new graphical techniques for multimodal integration of neuroimaging data as well as new approaches based on Riemannian statistics for covariance-based classification. My next research endeavor is to develop new multivariate methods for high dimensional, multiresponse prediction to investigate the relationships between genetics, brain, and behaviour. Importantly, to facilitate result interpretation, I plan to pursue research in high dimensional hypothesis testing and develop new statistical techniques for identifying significant predictors from high dimensional prediction models.

Publications

Publications

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