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Abstract:

Mental disorders are a leading cause of disability worldwide, yet current symptom-based diagnoses remain subjective and imprecise. Advances in neuroimaging now enable large-scale, non-invasive brain data collection, creating opportunities for objective, data-driven biomarkers.

Leveraging EEG and fMRI, our research applies cutting-edge machine learning to decode neural patterns, model brain connectomes, and identify latent neurobiotypes. I will present recent work on latent-space biomarker quantification, predictive brain network modeling, and unsupervised disease biotyping, aiming toward precision diagnosis and personalized treatment in mental health.

Dr Zhang’s biography is available here: https://hai.stanford.edu/people/yu-zhang