David van Dijk
Biography
Research & Publications
News
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 FellowColumbia University (2015)
- PhDUniversity of Amsterdam, Computer Science (2013)
- Postdoctoral FellowWeizmann Institute of Science (2013)
- MScFree University of Amsterdam, Computer Science (2008)
- BScFree University of Amsterdam, Computer Science (2005)
Activities
- Manifold learning uncovers hidden structure in complex cellular state spaceUtrecht, UT, Netherlands 2019Manifold learning uncovers hidden structure in complex cellular state space
- Manifold learning uncovers hidden structure in complex cellular state spaceLausanne, VD, Switzerland 2019Department seminar
- Manifold learning uncovers hidden structure in complex cellular state spaceNew York, NY, United States 2019Manifold learning uncovers hidden structure in complex cellular state space
- Predicting gene expression from DNA sequenceBarcelona, CT, Spain 2013Department seminar
Honors & Recognition
Award | Awarding Organization | Date |
---|---|---|
NIH R35 MIRA award ($1.25M) | 2021 | |
Best Paper Award ICML conference GRL+ workshop | International Conference On Machine Learning (ICML) | 2020 |
NWO (Netherlands Scientific Organization) Rubicon Postdoctoral Fellowship Award (€130k) | NWO (Netherlands Scientific Organization) | 2015 |
Azrieli Fellowship Award | Azrieli Foundation | 2013 |
Weizmann Postdoctoral Fellowship | Weizmann Institute of Science | 2012 |
EMBO (Excellence In Life Sciences) Short Term Fellowship | EMBO (Excellence In Life Sciences) | 2010 |
Netherlands Bioinformatics Center Fellowship | Neherlands Bioinformatics Center | 2010 |
DECOI Conference Data Mining Competition 2007 1st Place | DECOI | 2007 |
VU Data Mining Competition 1st Place | VU | 2007 |
Professional Service
Organization | Role | Date |
---|---|---|
Yale CBB program | PhD qualifying committee member for Eric Ni, Yale CBB program | 2022 - Present |
Departments & Organizations
- Cardiovascular Medicine
- Center for Biomedical Data Science
- Center for Infection and Immunity
- Center for RNA Science and Medicine
- Computational Biology and Bioinformatics Track
- Interdepartmental Neuroscience Program
- Internal Medicine
- Neuroscience Track
- Wu Tsai Institute
- Yale Cardiovascular Research Center (YCVRC)
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)