Deep Probabilistic Models for Personalized Psychiatry (DC8)

This project applies deep probabilistic neural networks (DPNNs) to major depressive disorder, using genetic, clinical, and environmental data to create predictive models for diagnosis and treatment planning. The researcher will enhance model robustness and interpretability by incorporating structured priors and rectified factor networks. The goal is to identify which biological factors drive depression in different individuals, enabling precision psychiatry informed by both data and clinical expertise.