David van Dijk, PhD

The van Dijk Lab focuses on the development of new machine learning algorithms for large biomedical datasets. Their approaches aim to discover hidden structures, signals, and patterns in complex high-dimensional and high-throughput data, including single-cell RNA sequencing, electronic health records, biomedical imaging, and brain activity recordings. In recent work, they have been using computer vision and natural language processing techniques to encode large-scale spatio-temporal brain activity recordings, including mesoscopic calcium imaging and fMRI recordings.

deep learning ;  dimensionality reduction ;  dynamical systems ;  graph theory ;  manifold learning ;  signal processing  

algorithms ;  artificial intelligence ;  computational biology ;  machine intelligence ;  machine learning ;  predictive modeling  

David van Dijk is an Assistant Professor of Medicine and of Computer Science. He received his PhD in Computer Science from the University of Amsterdam. Dr. van Dijk was a Rubicon postdoctoral fellow at the Weizmann Institute of Science and Columbia University. In 2019, he opened a biomedical machine learning lab at Yale in the Department of Internal Medicine and the Department of Computer Science. He is the recipient of the NIH MIRA award. He enjoys hiking, building furniture, and making art in his free time.