World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
37
Citations
6516
World Ranking
2479
National Ranking
1036

Computer Science

D-Index
37
Citations
6443
World Ranking
10675
National Ranking
4466

Thomas S. Richardson 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 Thomas S. Richardson 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+

This scientist: 126 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

Thomas S. Richardson 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 Thomas S. Richardson 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+

This scientist: 37 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Thomas S. Richardson is affiliated with the University of Washington in the United States. Their research primarily focuses on the field of Mathematics, with extensive work related to Statistics and Probability.

The scientist's research spans several subfields including:

  • Statistics and Probability
  • Artificial Intelligence
  • Economics and Econometrics
  • Atomic and Molecular Physics, and Optics
  • General Health Professions

Key topics explored in Richardson's work include:

  • Advanced Causal Inference Techniques
  • Statistical Methods and Bayesian Inference
  • Statistical Methods and Inference
  • Bayesian Modeling and Causal Inference
  • Statistical Methods in Clinical Trials
  • Health Systems, Economic Evaluations, Quality of Life
  • Health Policy Implementation Science

Richardson has contributed to a number of recent papers, such as:

  • "Nested Markov properties for acyclic directed mixed graphs," 2023, The Annals of Statistics
  • "Estimation of local treatment effects under the binary instrumental variable model," 2021, Biometrika
  • "Experimental Design in Marketplaces," 2023, Statistical Science
  • "Foundations and new horizons for causal inference," 2020, Oberwolfach Reports
  • "An Interventionist Approach to Mediation Analysis," 2020, arXiv (Cornell University)

The scientist frequently publishes in venues including:

  • arXiv (Cornell University)
  • Biometrika
  • Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • The Annals of Statistics
  • Statistical Science

Collaborations play a significant role in their research, with frequent co-authors including:

  • James M. Robins
  • Ilya Shpitser
  • James M. McQueen
  • F Richard Guo
  • Linbo Wang

Best Publications

  • Ancestral graph Markov models

    Thomas Richardson;Peter Spirtes

  • Learning high-dimensional directed acyclic graphs with latent and selection variables

    Diego Colombo;Marloes H. Maathuis;Markus Kalisch;Thomas S. Richardson

  • Chain graph models and their causal interpretations

    Steffen Lilholt Lauritzen;Thomas S. Richardson

  • The TETRAD project: Constraint based aids to causal model specification.

    Richard Scheines;Peter Spirtes;Clark Glymour;Christopher Meek

  • Demystifying Optimal Dynamic Treatment Regimes

    Erica E. M. Moodie;Thomas S. Richardson;David A. Stephens

  • An Evaluation of Machine-Learning Methods for Predicting Pneumonia Mortality

    Gregory F. Cooper;Constantin F. Aliferis;Richard Ambrosino;John M. Aronis

  • Causal inference in the presence of latent variables and selection bias

    Peter Spirtes;Christopher Meek;Thomas Richardson

  • Markov Properties for Acyclic Directed Mixed Graphs

    Thomas Richardson

  • Alternative Graphical Causal Models and the Identification of Direct E!ects

    James Robins;Thomas Richardson

  • A discovery algorithm for directed cyclic graphs

    Thomas Richardson

  • Covariate selection for the nonparametric estimation of an average treatment effect

    Xavier De Luna;Ingeborg Waernbaum;Thomas S. Richardson

  • Estimation of a covariance matrix with zeros

    Sanjay Chaudhuri;Mathias Drton;Thomas S. Richardson

  • Using path diagrams as a structural equation modeling tool

    Peter Spirtes;Thomas Richardson;Christopher Meek;Richard Scheines

  • Boosting methodology for regression problems.

    Greg Ridgeway;David Madigan;Thomas Richardson

  • An Algorithm for causal inference in the presence of latent variables and selection bias

    P. Spirtes;C. Meek;T. Richardson;Chris Meek

  • Interpretable boosted naïve Bayes classification

    Greg Ridgeway;David Madigan;Thomas Richardson;John O'Kane

  • MARKOV EQUIVALENCE FOR ANCESTRAL GRAPHS

    R. Ayesha Ali;Thomas S. Richardson;Peter Spirtes

  • Partial Identification of the Average Treatment Effect Using Instrumental Variables: Review of Methods for Binary Instruments, Treatments, and Outcomes

    Sonja A. Swanson;Sonja A. Swanson;Miguel A. Hernán;Miguel A. Hernán;Matthew Miller;Matthew Miller;James M. Robins

  • Automated discovery of linear feedback models

    Thomas Richardson;Peter Spirtes

  • Estimating Optimal Dynamic Regimes: Correcting Bias under the Null

    Erica E. M. Moodie;Thomas S. Richardson

  • Nested Markov properties for acyclic directed mixed graphs

    Thomas S. Richardson;James M. Robins;Ilya Shpitser

Frequent Co-Authors

James M. Robins
James M. Robins Harvard University
Peter Spirtes
Peter Spirtes Carnegie Mellon University
Robin J. Evans
Robin J. Evans University of Melbourne
Mathias Drton
Mathias Drton Technical University of Munich
Clark Glymour
Clark Glymour Carnegie Mellon University
David Madigan
David Madigan Northeastern University
Richard Scheines
Richard Scheines Carnegie Mellon University
Tyler J. VanderWeele
Tyler J. VanderWeele Harvard University
Steffen L. Lauritzen
Steffen L. Lauritzen University of Copenhagen
Jon Wakefield
Jon Wakefield University of Washington

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