David Van Dijk

David Van Dijk is an Assistant Professor in the Department of Computer Science at Yale University. His research focuses on advancing artificial intelligence and large-scale foundation models for biomedicine, integrating mathematics, machine learning, and genomic data to uncover biological processes. His work includes developing multiscale foundation models, spatiotemporal dynamical systems, and causal inference methods. Van Dijk's lab has presented at major conferences such as NeurIPS, ICLR, and has published in top-tier journals. His research spans from single-cell analysis to organ-level modeling, with applications in cancer, autoimmune disease, and tissue regeneration. He is also involved in projects like Cell2Sentence and CINEMA-OT, which aim to improve the interpretability and performance of machine learning models in biomedical contexts.

David van Dijk is an Assistant Professor at Yale University specializing in machine learning and computational biology. His research focuses on developing advanced computational methods to analyze complex biological data, particularly in the context of single-cell genomics and immunology. His work includes the application of machine learning techniques to uncover gene interactions, model cellular dynamics, and identify biomarkers for diseases such as COVID-19. Van Dijk's research also explores the integration of multi-omics data to understand immune responses and disease progression. His publications highlight the use of deep learning, diffusion models, and manifold learning to address challenges in single-cell RNA-sequencing and other high-dimensional biological datasets.