David van Dijk, PhD

Dr. David van Dijk completed his PhD in Computer Science at the University of Amsterdam and the Weizmann Institute of Science where he used machine learning to decipher links between DNA sequence and gene activity. Dr. van Dijk moved on to postdoctoral fellow positions at Columbia University and Yale University where he developed manifold learning and machine learning algorithms for single-cell genomic data. Dr. van Dijk is currently an Assistant Professor in the departments of Computer Science and Internal Medicine at Yale University where his lab specializes in developing machine learning algorithms, inspired by ideas from computer vision and natural language processing, that are capable of analyzing large biomedical datasets, including single-cell RNA sequencing, health records, medical imaging, and brain activity data. Dr. van Dijk is recipient of the Dutch Research Council Rubicon fellowship and the NIH R35 Maximizing Investigators’ Research Award

Yale University | New Haven, USA

David van Dijk, PhD

Yale University | New Haven, USA

Dr. David van Dijk completed his PhD in Computer Science at the University of Amsterdam and the Weizmann Institute of Science where he used machine learning to decipher links between DNA sequence and gene activity. Dr. van Dijk moved on to postdoctoral fellow positions at Columbia University and Yale University where he developed manifold learning and machine learning algorithms for single-cell genomic data. Dr. van Dijk is currently an Assistant Professor in the departments of Computer Science and Internal Medicine at Yale University where his lab specializes in developing machine learning algorithms, inspired by ideas from computer vision and natural language processing, that are capable of analyzing large biomedical datasets, including single-cell RNA sequencing, health records, medical imaging, and brain activity data. Dr. van Dijk is recipient of the Dutch Research Council Rubicon fellowship and the NIH R35 Maximizing Investigators’ Research Award