Towards Machine Learning-Driven Precision Mental Health

Monday, March 22, 2021 - 12:00pm to 1:00pm

Topic: Dr. Wei Wu's Seminar

Time: Mar 22, 2021 12:00 PM Eastern Time (US and Canada)

Dr. Wei Wu is a candidate for the AI-Neuroscience Faculty position.

Abstract: Psychiatric disorders are major causes of the global burden of disease affecting more than 1 billion people globally. Current psychiatric diagnoses are defined based on constellations of symptoms. However, patients with identical diagnoses may in fact fall into biologically heterogeneous subgroups, each of which may require a different therapy. Yet to date, we still lack validated neurobiological biomarkers that can reliably dissect such heterogeneity and allow us to objectively diagnose and treat psychiatric disorders. In this talk, I will present our recent discoveries of EEG biomarkers for dissecting the biological heterogeneity of psychiatric disorders, enabled by tailed machine learning methods for decoding disease-relevant information from EEG. These biomarkers can also be leveraged to drive therapeutic development using brain stimulation tools. Our findings therefore lay a path towards machine-learning driven personalized treatment to psychiatric disorders and have the potential of being translated to the clinic as point-of-care biological tests.

Short Bio: Wei Wu is the Co-Founder and Chief Technology Officer of Alto Neuroscience, Inc., Los Altos, CA. He is also an Instructor affiliated with the Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA. He received the Ph.D. degree in Biomedical Engineering from Tsinghua University, Beijing, China, in 2012. From 2012-2016, he was an Associate Professor with the School of Automation Science and Engineering, South China University of Technology, Guangzhou, China. His research interests include computational psychiatry, brain signal processing, neural engineering, and brain stimulation. Dr. Wu is an IEEE Senior Member, an Associate Editor of Neural Processing Letters and Frontiers in Computational Neuroscience, and served as an Associate Editor of Neurocomputing from 2013-2019. He is also a member of the IEEE Biomedical Signal Processing Technical Committee. Homepage:

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