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INFORMATION FOR

David van Dijk

PhD, MSc, BSc
Assistant Professor

Contact Information

David van Dijk, PhD, MSc, BSc

Mailing Address

  • Yale School of Medicine

    300 George Street, 2nd Floor, rm 2312

    New Haven, Connecticut 06511

    United States

Appointments

Biography

Dr. David van Dijk is Assistant Professor at Yale Dept. of Internal Medicine and Yale Dept. of Computer Science where he leads a research group that focuses on the cutting-edge application of machine learning methods to big biomedical data. His group develops new algorithms for discovering hidden structure, signals, and patterns in complex high-dimensional and high-throughput data, including single-cell RNA sequencing, microbiome, medical imaging, and electronic health records. His research team comprises trainees from diverse backgrounds, including computer science, mathematics, physics, biology, medicine, and neuroscience. Dr. 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 understand how gene regulation is encoded in DNA sequence. As a postdoc at Yale Genetics and Computer Science, he developed machine learning methods for single-cell data that are widely used in the biomedical community.

Website: vandijklab.org

Education & Training

  • Postdoctoral Fellow
    Columbia University (2015)
  • PhD
    University of Amsterdam, Computer Science (2013)
  • Postdoctoral Fellow
    Weizmann Institute of Science (2013)
  • MSc
    Free University of Amsterdam, Computer Science (2008)
  • BSc
    Free University of Amsterdam, Computer Science (2005)

Activities

  • Manifold learning uncovers hidden structure in complex cellular state space
    Utrecht, UT, Netherlands 2019
    Manifold learning uncovers hidden structure in complex cellular state space
  • Manifold learning uncovers hidden structure in complex cellular state space
    Lausanne, VD, Switzerland 2019
    Department seminar
  • Manifold learning uncovers hidden structure in complex cellular state space
    New York, NY, United States 2019
    Manifold learning uncovers hidden structure in complex cellular state space
  • Predicting gene expression from DNA sequence
    Barcelona, CT, Spain 2013
    Department seminar

Honors & Recognition

AwardAwarding OrganizationDate
NIH R35 MIRA award ($1.25M)2021
Best Paper Award ICML conference GRL+ workshopInternational Conference On Machine Learning (ICML)2020
NWO (Netherlands Scientific Organization) Rubicon Postdoctoral Fellowship Award (€130k)NWO (Netherlands Scientific Organization)2015
Azrieli Fellowship AwardAzrieli Foundation2013
Weizmann Postdoctoral FellowshipWeizmann Institute of Science2012
EMBO (Excellence In Life Sciences) Short Term FellowshipEMBO (Excellence In Life Sciences)2010
Netherlands Bioinformatics Center FellowshipNeherlands Bioinformatics Center2010
DECOI Conference Data Mining Competition 2007 1st PlaceDECOI2007
VU Data Mining Competition 1st PlaceVU2007

Professional Service

OrganizationRoleDate
Yale CBB programPhD qualifying committee member for Eric Ni, Yale CBB program2022 - Present

Departments & Organizations