World's Best Scientists 2026 revealed!

Joris M. Mooij publication distribution in Mathematics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Joris M. Mooij sits on this spectrum.

42–46 publications: 3 scientists 47–51 publications: 5 scientists 52–56 publications: 7 scientists 57–61 publications: 20 scientists 62–66 publications: 14 scientists 67–71 publications: 25 scientists 72–76 publications: 19 scientists 77–81 publications: 35 scientists 82–86 publications: 50 scientists 87–91 publications: 60 scientists 92–96 publications: 86 scientists 97–101 publications: 84 scientists 102–106 publications: 83 scientists 107–111 publications: 90 scientists 112–116 publications: 99 scientists 117–121 publications: 90 scientists 122–126 publications: 91 scientists 127–131 publications: 109 scientists 132–136 publications: 110 scientists 137–141 publications: 98 scientists 142–146 publications: 112 scientists 147–151 publications: 102 scientists 152–156 publications: 88 scientists 157–161 publications: 106 scientists 162–166 publications: 83 scientists 167–171 publications: 102 scientists 172–176 publications: 77 scientists 177–181 publications: 81 scientists 182–186 publications: 78 scientists 187–191 publications: 71 scientists 192–196 publications: 92 scientists 197–201 publications: 64 scientists 202–206 publications: 69 scientists 207–211 publications: 64 scientists 212–216 publications: 62 scientists 217–221 publications: 58 scientists 222–226 publications: 53 scientists 227–231 publications: 50 scientists 232–236 publications: 46 scientists 237–241 publications: 46 scientists 242–246 publications: 46 scientists 247–251 publications: 43 scientists 252–256 publications: 29 scientists 257–261 publications: 45 scientists 262–266 publications: 30 scientists 267–271 publications: 33 scientists 272–276 publications: 34 scientists 277–281 publications: 30 scientists 282–286 publications: 31 scientists 287–291 publications: 21 scientists 292–296 publications: 34 scientists 297–301 publications: 26 scientists 302–306 publications: 10 scientists 307–311 publications: 17 scientists 312–316 publications: 23 scientists 317–321 publications: 13 scientists 322–326 publications: 16 scientists 327–331 publications: 26 scientists 332–336 publications: 13 scientists 337–341 publications: 13 scientists 342–346 publications: 16 scientists 347–351 publications: 17 scientists 352–356 publications: 12 scientists 357–361 publications: 18 scientists 362–366 publications: 18 scientists 367–371 publications: 9 scientists 372–376 publications: 11 scientists 377–381 publications: 8 scientists 382–386 publications: 8 scientists 387–391 publications: 9 scientists 392–396 publications: 9 scientists 397–401 publications: 8 scientists 402–406 publications: 11 scientists 407–411 publications: 6 scientists 412–416 publications: 6 scientists 417–421 publications: 9 scientists 422–426 publications: 8 scientists 427–431 publications: 5 scientists 432–436 publications: 8 scientists 437–441 publications: 8 scientists 442–446 publications: 4 scientists 447–451 publications: 4 scientists 452–456 publications: 4 scientists 457–461 publications: 2 scientists 462–466 publications: 2 scientists 467–471 publications: 4 scientists 472–476 publications: 3 scientists 477–481 publications: 3 scientists 482–486 publications: 6 scientists 487–491 publications: 3 scientists 492–496 publications: 5 scientists 497–501 publications: 5 scientists 502–506 publications: 1 scientists 507–511 publications: 6 scientists 512–516 publications: 4 scientists 517–521 publications: 1 scientists 522–526 publications: 3 scientists 527–531 publications: 1 scientists 532–536 publications: 4 scientists 537+ publications: 100 scientists
42 publications 537+

The last bar groups every scientist with 537 publications or more.

Joris M. Mooij D-index placement in Mathematics in 2026

The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Joris M. Mooij sits on this spectrum.

30 D-Index: 174 scientists 31 D-Index: 151 scientists 32 D-Index: 174 scientists 33 D-Index: 117 scientists 34 D-Index: 136 scientists 35 D-Index: 127 scientists 36 D-Index: 145 scientists 37 D-Index: 153 scientists 38 D-Index: 150 scientists 39 D-Index: 150 scientists 40 D-Index: 138 scientists 41 D-Index: 136 scientists 42 D-Index: 93 scientists 43 D-Index: 108 scientists 44 D-Index: 115 scientists 45 D-Index: 112 scientists 46 D-Index: 103 scientists 47 D-Index: 75 scientists 48 D-Index: 59 scientists 49 D-Index: 67 scientists 50 D-Index: 60 scientists 51 D-Index: 57 scientists 52 D-Index: 59 scientists 53 D-Index: 62 scientists 54 D-Index: 60 scientists 55 D-Index: 50 scientists 56 D-Index: 42 scientists 57 D-Index: 54 scientists 58 D-Index: 50 scientists 59 D-Index: 42 scientists 60 D-Index: 41 scientists 61 D-Index: 35 scientists 62 D-Index: 40 scientists 63 D-Index: 21 scientists 64 D-Index: 31 scientists 65 D-Index: 27 scientists 66 D-Index: 29 scientists 67 D-Index: 19 scientists 68 D-Index: 25 scientists 69 D-Index: 17 scientists 70 D-Index: 18 scientists 71 D-Index: 12 scientists 72 D-Index: 14 scientists 73 D-Index: 13 scientists 74 D-Index: 18 scientists 75 D-Index: 9 scientists 76 D-Index: 11 scientists 77 D-Index: 10 scientists 78 D-Index: 9 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 10 scientists 82 D-Index: 5 scientists 83 D-Index: 5 scientists 84 D-Index: 13 scientists 85 D-Index: 6 scientists 86+ D-Index: 99 scientists
30 D-Index 86+

The last bar groups every scientist with 86 D-Index or more.

Overview

Joris M. Mooij is affiliated with the University of Amsterdam in the Netherlands. Their research primarily falls within the field of Computer Science with a focus on several subfields including Artificial Intelligence, Statistics and Probability, Molecular Biology, Management Science and Operations Research, and Computational Theory and Mathematics.

The scientist's main topics of work span a number of areas related to causal inference and computational methods. These include:

  • Bayesian Modeling and Causal Inference
  • Advanced Graph Neural Networks
  • Gene Regulatory Network Analysis
  • Logic, Reasoning, and Knowledge
  • Data Quality and Management
  • Statistical Methods and Inference
  • Protein Structure and Dynamics

Mooij has contributed extensively to the academic community with numerous publications. Key recent papers by the scientist include:

  • Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles, 2020, arXiv (Cornell University)
  • Causal Bandits without prior knowledge using separating sets, 2020, arXiv (Cornell University)
  • Local Constraint-Based Causal Discovery under Selection Bias, 2022, arXiv (Cornell University)
  • A Weaker Faithfulness Assumption based on Triple Interactions, 2020, arXiv (Cornell University)

Mooij's work appears frequently in the venue arXiv (Cornell University), with 21 publications, and also in the Journal of Causal Inference. Their collaborative network includes several frequent co-authors such as Philip Boeken, Tineke Blom, Onno Zoeter, Tom Claassen, and Patrick Forré.

Best Publications

  • MAGMA: Generalized Gene-Set Analysis of GWAS Data

    Christiaan A. de Leeuw;Joris M. Mooij;Tom Heskes;Danielle Posthuma

  • Nonlinear causal discovery with additive noise models

    Patrik O. Hoyer;Dominik Janzing;Joris M. Mooij;Jonas Peters

  • Causal discovery with continuous additive noise models

    Jonas Peters;Joris M. Mooij;Dominik Janzing;Bernhard Schölkopf

  • Causal Effect Inference with Deep Latent-Variable Models

    Christos Louizos;Uri Shalit;Joris M. Mooij;David A. Sontag

  • Distinguishing cause from effect using observational data: methods and benchmarks

    Joris M. Mooij;Jonas Peters;Dominik Janzing;Jakob Zscheischler

  • On causal and anticausal learning

    Dominik Janzing;Jonas Peters;Eleni Sgouritsa;Kun Zhang

  • libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models

    Joris M. Mooij

  • Information-geometric approach to inferring causal directions

    Dominik Janzing;Joris Mooij;Kun Zhang;Jan Lemeire

  • Sufficient Conditions for Convergence of the Sum–Product Algorithm

    J.M. Mooij;H.J. Kappen

  • On Causal and Anticausal Learning

    Bernhard Schoelkopf;Dominik Janzing;Jonas Peters;Eleni Sgouritsa

  • Inferring deterministic causal relations

    Povilas Daniušis;Dominik Janzing;Joris Mooij;Jakob Zscheischler

  • Methods for causal inference from gene perturbation experiments and validation.

    Nicolai Meinshausen;Alain Hauser;Joris M. Mooij;Jonas Peters

  • Regression by dependence minimization and its application to causal inference in additive noise models

    Joris Mooij;Dominik Janzing;Jonas Peters;Bernhard Schölkopf

  • Probabilistic latent variable models for distinguishing between cause and effect

    Oliver Stegle;Dominik Janzing;Kun Zhang;Joris M. Mooij

  • Identifiability of causal graphs using functional Models

    Jonas Peters;Joris M. Mooij;Dominik Janzing;Bernhard Schölkopf

  • Remote Sensing Feature Selection by Kernel Dependence Measures

    G Camps-Valls;J Mooij;B Scholkopf

  • Efficient inference in matrix-variate Gaussian models with iid observation noise

    Oliver Stegle;Christoph Lippert;Joris M. Mooij;Neil D. Lawrence

  • Learning sparse causal models is not NP-hard

    Tom Claassen;Joris M. Mooij;Tom Heskes

  • On Causal Discovery with Cyclic Additive Noise Models

    Joris M. Mooij;Dominik Janzing;Tom Heskes;Bernhard Schölkopf

  • From ordinary differential equations to structural causal models: the deterministic case

    Joris M. Mooij;Dominik Janzing;Bernhard Schölkopf

Frequent Co-Authors

Dominik Janzing
Dominik Janzing Amazon (United States)
Bernhard Schölkopf
Bernhard Schölkopf Max Planck Institute for Intelligent Systems
Hilbert J. Kappen
Hilbert J. Kappen Radboud University
Tom Heskes
Tom Heskes Radboud University
Kun Zhang
Kun Zhang Carnegie Mellon University
Jakob Zscheischler
Jakob Zscheischler Helmholtz Centre for Environmental Research
Max Welling
Max Welling University of Amsterdam
Oliver Stegle
Oliver Stegle German Cancer Research Center
Arthur Gretton
Arthur Gretton University College London

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Mathematics opens doors to various interdisciplinary career paths, including data science, finance, and technology. Many students consider enhancing their credentials with advanced degrees that complement their math background.

For those interested in leadership and management roles, pursuing an MBA can be a strategic choice. Several programs offer flexibility, and the option to can you transfer MBA credits is crucial for students looking to save time and money. This enables learners to build upon previous coursework seamlessly.

Data-driven fields are booming, making a data analytics master's degree a valuable pursuit for math graduates. These programs emphasize practical skills and analytical techniques essential for interpreting complex datasets.

Some students prioritize ease of admission and quick completion when choosing further education. Exploring options described in the easiest MBA to get into and easiest and fastest online MBA programs articles can help identify schools that match these criteria without compromising quality.

Best Scientists Citing Joris M. Mooij

Trending Scientists

Recently Published Articles