David van Dijk, PhD, MSc, BSc
Assistant Professor of Medicine (Cardiovascular Medicine) and of Computer ScienceDownloadHi-Res Photo
Cards
Appointments
Cardiovascular Medicine
Primary
Contact Info
Yale School of Medicine
300 George Street, 2nd Floor, rm 2312
New Haven, Connecticut 06511
United States
About
Titles
Assistant Professor of Medicine (Cardiovascular Medicine) and of Computer Science
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
Appointments
Cardiovascular Medicine
Assistant ProfessorPrimary
Other Departments & Organizations
- Cardiovascular Medicine
- Center for Biomedical Data Science
- Center for Infection and Immunity
- Center for RNA Science and Medicine
- Computational Biology and Biomedical Informatics
- 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)
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)
Research
Overview
Medical Research Interests
Computational Biology; Deep Learning; Machine Learning; Neurosciences; Single-Cell Analysis
ORCID
0000-0003-3911-9925- View Lab Website
David van Dijk
Research at a Glance
Yale Co-Authors
Frequent collaborators of David van Dijk's published research.
Publications Timeline
A big-picture view of David van Dijk's research output by year.
Research Interests
Research topics David van Dijk is interested in exploring.
David A. Hafler, MD, FANA
Akiko Iwasaki, PhD
F. Perry Wilson, MD, MSCE
Ruth R Montgomery, PhD
Smita Krishnaswamy, PhD
Craig B. Wilen, MD, PhD
58Publications
6,741Citations
Single-Cell Analysis
Computational Biology
Machine Learning
Deep Learning
Publications
2024
Learning Integral Operators with Neural Integral Equations
Zappala, E., Fonseca, A. H. D. O., Caro, J. O., & van Dijk, D. (2022). Neural integral equations. arXiv preprint arXiv:2209.15190. (published at Nature Machine Intelligence)Peer-Reviewed Original ResearchBrainLM: A foundation model for brain activity recordings
Ortega Caro, J., Oliveira Fonseca, A. H., Averill, C., Rizvi, S. A., Rosati, M., Cross, J. L., ... & van Dijk, D. (2023). BrainLM: A foundation model for brain activity recordings. bioRxiv, 2023-09. (Published at ICLR 2024)Peer-Reviewed Original ResearchCell2sentence: Teaching large language models the language of biology
Levine, D., Lévy, S., Rizvi, S. A., Pallikkavaliyaveetil, N., Chen, X., Zhang, D., ... & van Dijk, D. (2023). Cell2sentence: Teaching large language models the language of biology. bioRxiv, 2023-09. (Published at ICML 2024)Peer-Reviewed Original Research
2023
scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles
Zhu B, Wang Y, Ku L, van Dijk D, Zhang L, Hafler D, Zhao H. scNAT: a deep learning method for integrating paired single-cell RNA and T cell receptor sequencing profiles. Genome Biology 2023, 24: 292. PMID: 38111007, PMCID: PMC10726524, DOI: 10.1186/s13059-023-03129-y.Peer-Reviewed Original ResearchCitationsAltmetricLongitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1
Tejwani L, Ravindra N, Lee C, Cheng Y, Nguyen B, Luttik K, Ni L, Zhang S, Morrison L, Gionco J, Xiang Y, Yoon J, Ro H, Haidery F, Grijalva R, Bae E, Kim K, Martuscello R, Orr H, Zoghbi H, McLoughlin H, Ranum L, Shakkottai V, Faust P, Wang S, van Dijk D, Lim J. Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1. Neuron 2023, 112: 362-383.e15. PMID: 38016472, PMCID: PMC10922326, DOI: 10.1016/j.neuron.2023.10.039.Peer-Reviewed Original ResearchCitationsAltmetricCausal identification of single-cell experimental perturbation effects with CINEMA-OT
Dong M, Wang B, Wei J, de O. Fonseca A, Perry C, Frey A, Ouerghi F, Foxman E, Ishizuka J, Dhodapkar R, van Dijk D. Causal identification of single-cell experimental perturbation effects with CINEMA-OT. Nature Methods 2023, 20: 1769-1779. PMID: 37919419, PMCID: PMC10630139, DOI: 10.1038/s41592-023-02040-5.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsAnatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling
Golan N, Ehrlich D, Bonanno J, O'Brien R, Murillo M, Kauer S, Ravindra N, Van Dijk D, Cafferty W. Anatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling. Journal Of Neuroscience 2023, 43: 7929-7945. PMID: 37748862, PMCID: PMC10669816, DOI: 10.1523/jneurosci.0811-22.2023.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsCorticospinal tract neuronsCorticospinal tractAdult corticospinal tractIrreversible functional deficitsCortical layer 2/3Lumbar spinal cordSpinal cord injuryLayer 5 neuronsClasses of neuronsMolecular heterogeneityAxon collateralizationTract neuronsCord injuryRetrograde labelingMotor pathwaysFemale miceFunctional deficitsLayer 2/3Primary axonsSpinal cordTerminal fieldsNeuron subtypesAdult tractTherapeutic interventionsSingle-cell RNA sequencingDistinguishing features of long COVID identified through immune profiling
Klein J, Wood J, Jaycox J, Dhodapkar R, Lu P, Gehlhausen J, Tabachnikova A, Greene K, Tabacof L, Malik A, Silva Monteiro V, Silva J, Kamath K, Zhang M, Dhal A, Ott I, Valle G, Peña-Hernández M, Mao T, Bhattacharjee B, Takahashi T, Lucas C, Song E, McCarthy D, Breyman E, Tosto-Mancuso J, Dai Y, Perotti E, Akduman K, Tzeng T, Xu L, Geraghty A, Monje M, Yildirim I, Shon J, Medzhitov R, Lutchmansingh D, Possick J, Kaminski N, Omer S, Krumholz H, Guan L, Dela Cruz C, van Dijk D, Ring A, Putrino D, Iwasaki A. Distinguishing features of long COVID identified through immune profiling. Nature 2023, 623: 139-148. PMID: 37748514, PMCID: PMC10620090, DOI: 10.1038/s41586-023-06651-y.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsLong COVIDSARS-CoV-2Infection syndromeExaggerated humoral responseSoluble immune mediatorsEpstein-Barr virusPost-exertional malaiseCross-sectional studyHigher antibody responseImmune mediatorsImmune phenotypingImmune profilingHumoral responseAntibody responseLymphocyte populationsCOVID statusUnbiased machineCortisol levelsLC statusRelevant biomarkersViral pathogensSyndromeCOVIDFuture studiesBiological featuresContinuous Spatiotemporal Transformer
Fonseca, A. H. D. O., Zappala, E., Caro, J. O., & Van Dijk, D. (2023, July). Continuous Spatiotemporal Transformer. In International Conference on Machine Learning (pp. 7343-7365). PMLR.Peer-Reviewed Original ResearchNeural Integro-Differential Equations
Zappala E, de O. Fonseca A, Moberly A, Higley M, Abdallah C, Cardin J, Van Dijk D. Neural Integro-Differential Equations. Proceedings Of The AAAI Conference On Artificial Intelligence 2023, 37: 11104-11112. DOI: 10.1609/aaai.v37i9.26315.Peer-Reviewed Original ResearchCitationsAltmetricConceptsIntegro-differential equationsIntegral operatorsDifferential equationsContinuous dynamical systemsNon-local dynamicsDynamical systemsInitial conditionsEquationsNeural networkTime extrapolationOperatorsIntegralsFundamental problemSuch dynamicsLatent spaceDynamicsNon-local processesBrain activity recordingsBrain dynamicsData scienceDifferential componentsIntegrandGeneralizationTheoryNetwork
Academic Achievements & Community Involvement
activity Yale CBB program
CommitteesCommittee MemberDetailsPhD qualifying committee member for Eric Ni, Yale CBB program2022 - Presentactivity CBB/BIDS Seminar Series
Meeting Planning and ParticipationCo-OrganizerDetails09/01/2022 - Presentactivity Learning the Language of Biology
Oral PresentationBroad Institute of Harvard and MITDetails10/16/2024 - PresentCambridge, MA, United Statesactivity Learning the language of biology using foundation models for brains and cells
Oral PresentationUniversity of Tokyo IRCN SalonDetails09/03/2024 - 09/03/2024University of Tokyoactivity Cell2Sentence: Teaching Large Language Models the Language of Biology
Poster PresentationInternational Conference on Machine Learning (ICML) 2024Details07/24/2024 - PresentVienna, Vienna, AustriaCollaborators
Teaching & Mentoring
Mentoring
Emanuele Zappala
Postdoc2022 - 2024Neal Ravindra
Postdoc2019 - 2022Antonio Oliveira Fonseca
Graduate student2019 - 2024
News
News
- July 11, 2024Source: Yale Ventures
11 Yale Projects Receive Awards from the Colton Center for Autoimmunity
- November 27, 2023
Yale Researchers Shed Light on the Progression of Neurodegeneration
- November 02, 2023
Discovering the 'Cytokine Language' That Activates Immune Responses
- April 13, 2023
Discoveries & Impact (April 2023)
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Yale School of Medicine
300 George Street, 2nd Floor, rm 2312
New Haven, Connecticut 06511
United States