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David van Dijk is a leading researcher in the field of artificial intelligence and its applications in biomedicine. At Yale University's van Dijk Lab, he spearheads a team dedicated to advancing large-scale foundation models that leverage rigorous mathematics and state-of-the-art machine learning techniques. His work focuses on utilizing rich genomic and clinical data to uncover the fundamental rules governing life processes. The lab's innovative methods include creating digital twins for disease progression forecasting and employing cutting-edge neural operator learning to model complex biological dynamics. David's research interests span spatiotemporal dynamical systems, causal inference, and the integration of machine learning with traditional biological methods. He is committed to educational outreach and collaboration with clinicians, facilitating significant contributions to both biological and medical sciences.
Administered via the Graduate School of Arts and Sciences (GSAS). GRE General is optional for PhD.