World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
32
Citations
5544
World Ranking
3148
National Ranking
1261

Michael D. Perlman 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 Michael D. Perlman 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: 117 publications — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Michael D. Perlman 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 Michael D. Perlman 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: 32 D-Index — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Overview

Michael D. Perlman is a researcher affiliated with the University of Washington in the United States, specializing in mathematics. Their work primarily spans multiple interconnected fields within mathematics, with a significant focus on geometry, algebra, and combinatorics.

The main fields of study covered by their research include:

  • Mathematics

Within this broad domain, Perlman has contributed extensively to several subfields:

  • Geometry and Topology
  • Algebra and Number Theory
  • Discrete Mathematics and Combinatorics
  • Molecular Biology
  • Mathematical Physics

Their research addresses a variety of advanced topics, notably:

  • Algebraic structures and combinatorial models
  • Advanced Combinatorial Mathematics
  • Advanced Topics in Algebra
  • Commutative Algebra and Its Applications
  • Algebraic Geometry and Number Theory
  • Advanced Algebra and Geometry
  • Genomics and Chromatin Dynamics

Michael D. Perlman has published in a number of academic venues, with frequent contributions to:

  • arXiv (Cornell University)
  • OPAL (Open@LaTrobe) (La Trobe University)
  • Nucleus
  • Advances in Mathematics
  • Journal of Commutative Algebra

Their recent papers include:

  • "4DNvestigator: time series genomic data analysis toolbox," 2021, Nucleus
  • "4DNvestigator: time series genomic data analysis toolbox," 2021, OPAL (Open@LaTrobe) (La Trobe University)
  • "Relations between the 2 × 2 minors of a generic matrix," 2021, Advances in Mathematics
  • "Regularity and cohomology of Pfaffian thickenings," 2021, Journal of Commutative Algebra
  • "Equivariant resolutions over Veronese rings," 2023, Journal of the London Mathematical Society

Frequent collaborators in their research include:

  • Stephen Lindsly
  • Can Chen
  • Sijia Liu
  • Scott Ronquist
  • Samuel Dilworth

Best Publications

  • A characterization of Markov equivalence classes for acyclic digraphs

    Steen A. Andersson;David B. Madigan;Michael D. Perlman

  • One-Sided Testing Problems in Multivariate Analysis

    Michael D. Perlman

  • Model selection for Gaussian concentration graphs

    Mathias Drton;Michael D. Perlman

  • Alternative Markov Properties for Chain Graphs

    Steen A. Andersson;David Madigan;Michael D. Perlman

  • Bayesian model averaging and model selection for markov equivalence classes of acyclic digraphs

    David Madigan;Steen A. Andersson;Michael D. Perlman;Chris T. Volinsky

  • Multiple Testing and Error Control in Gaussian Graphical Model Selection

    Mathias Drton;Michael D. Perlman

  • A SINful approach to Gaussian graphical model selection

    Mathias Drton;Michael D. Perlman

  • The Non-Singularity of Generalized Sample Covariance Matrices

    Morris L. Eaton;Michael D. Perlman

  • The Emperor’s new tests

    Michael D. Perlman;Lang Wu

  • Inequalitites on the probability content of convex regions for elliptically contoured distributions

    S. Das Gupta;M. L. Eaton;I. Olkin;M. Perlman

  • Reflection Groups, Generalized Schur Functions, and the Geometry of Majorization

    Morris L. Eaton;Michael D. Perlman

  • Power of the Noncentral F-Test: Effect of Additional Variates on Hotelling's T2-Test

    Unknown

  • On the Markov Equivalence of Chain Graphs, Undirected Graphs, and Acyclic Digraphs

    Steen A. Andersson;David Madigan;Michael D. Perlman

  • Association of Normal Random Variables and Slepian's Inequality

    Kumar Jogdeo;Michael D Perlman;Loren D Pitt

  • Contributions to Probability and Statistics

    Leon Jay Gleser;Michael D. Perlman;S. James Press;Allan R. Sampson

  • Unbiasedness of the Likelihood Ratio Tests for Equality of Several Covariance Matrices and Equality of Several Multivariate Normal Populations

    Michael D. Perlman

  • Jensen's inequality for a convex vector-valued function on an infinite-dimensional space

    Unknown

  • On the strong consistency of approximate maximum likelihood estimators

    Michael D. Perlman

  • Lattice Models for Conditional Independence in a Multivariate Normal Distribution

    Steen Arne Andersson;Michael D. Perlman

  • Unbiasedness of Invariant Tests for Manova and Other Multivariate Problems

    Michael D. Perlman;Ingram Olkin

  • The size distribution for Markov equivalence classes of acyclic digraph models

    Steven B. Gillispie;Michael D. Perlman

  • Enumerating Markov Equivalence Classes of Acyclic Digraph Models

    Steven B. Gillispie;Michael D. Perlman

Frequent Co-Authors

David Madigan
David Madigan Northeastern University
Mathias Drton
Mathias Drton Technical University of Munich
Leon Jay Gleser
Leon Jay Gleser University of Pittsburgh
Mark Groudine
Mark Groudine Fred Hutchinson Cancer Research Center
Charles Kooperberg
Charles Kooperberg Fred Hutchinson Cancer Research Center
John A. Hansen
John A. Hansen Fred Hutchinson Cancer Research Center
Sijia Liu
Sijia Liu Michigan State University
Paul J. Martin
Paul J. Martin Fred Hutchinson Cancer Research Center
Jon A. Wellner
Jon A. Wellner University of Washington
Kathryn Roeder
Kathryn Roeder Carnegie Mellon University

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

For students pursuing Mathematics in the USA, exploring related online degrees can open diverse career pathways. Many professionals leverage their quantitative skills by opting for advanced studies like an one year mba program, which offers a fast-track to leadership roles in finance, technology, and analytics.

Transfer flexibility is also crucial for students balancing work and study. Programs such as mba programs that accept transfer credits provide valuable options to build on previously earned coursework without losing momentum.

For those interested in harnessing data-driven decision-making, an ms in data analytics is a natural complement to a mathematics foundation. These programs equip graduates with expertise in data mining, visualization, and predictive modeling.

Prospective students looking for accessible options can explore what mba programs can i get into to identify suitable entry points into the business world. Overall, combining mathematical skills with these online degrees expands career opportunities in sectors like finance, consulting, and technology.

Best Scientists Citing Michael D. Perlman

Trending Scientists

Recently Published Articles