David van Dijk, PhD, MSc, BSc

Dr. David van Dijk is an Assistant Professor in the departments of Computer Science and Internal Medicine at Yale University, where he leads research in developing advanced machine learning (ML) and artificial intelligence (AI) algorithms for large-scale biomedical data. His work integrates foundation models, large language models (LLMs), graph representation learning, and neural operator learning to analyze spatiotemporal biological systems. Dr. van Dijk earned his PhD in Computer Science from the University of Amsterdam and the Weizmann Institute of Science, focusing on ML techniques to understand the link between DNA sequence and gene activity. He completed postdoctoral training at Columbia University and Yale, specializing in manifold learning and single-cell genomic data analysis. Currently, Dr. van Dijk’s lab develops innovative AI methods for diverse biomedical applications, including single-cell RNA sequencing, electronic health records, medical imaging, and brain activity data. His research aims to uncover novel biological patterns, predict clinical outcomes, and drive advances in precision medicine. Dr. van Dijk’s contributions have been recognized with awards such as the Dutch Research Council Rubicon Fellowship, Colton Award, Roberts Innovation Award, NIH R35 MIRA Award, and NSF CAREER Award.