Research-pages

This pillar spans representation learning, AI algorithms for image analysis, and AI-enabled platforms that support translational imaging research - from foundational methods through to tools deployed on real clinical data.

We bring the methods above to bear on specific disease areas - Alzheimer’s disease, brain tumors, and psychiatric disorders - with the goal of personalized diagnostics and improved disease understanding.

The lab builds machine learning frameworks to model brain structure in health and disease across the lifespan, drawing on large-scale, multimodal neuroimaging datasets to capture heterogeneity in structure, function, and disease progression.