World's Best Scientists 2026 revealed!
Geoffrey J. McLachlan

Geoffrey J. McLachlan

Award Badge
Mathematics
Australia
2026

D-Index & Metrics

Mathematics

D-Index
65
Citations
69945
World Ranking
371
National Ranking
10

Engineering and Technology

D-Index
59
Citations
65360
World Ranking
2270
National Ranking
118

Geoffrey J. McLachlan 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 Geoffrey J. McLachlan 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: 377 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Geoffrey J. McLachlan 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 Geoffrey J. McLachlan 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: 65 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Mathematics in Australia Leader Award
  • 2025 - Research.com Mathematics in Australia Leader Award
  • 2023 - Research.com Mathematics in Australia Leader Award
  • 1998 - Fellow of the American Statistical Association (ASA)

Overview

Geoffrey J. McLachlan is affiliated with the University of Queensland in Australia and specializes in research spanning computer science and mathematics. The primary areas of their work include artificial intelligence, statistics and probability, mechanical engineering, computer vision and pattern recognition, and economics and econometrics.

The scientist's main research topics focus largely on Bayesian methods and mixture models as well as statistical methods and Bayesian inference. Other notable areas of investigation include statistical distribution estimation and applications, machine learning and data classification, mineral processing and grinding, and advanced statistical methods and models.

Geoffrey J. McLachlan has published extensively in various academic venues. The frequent publication outlets include:

  • arXiv (Cornell University)
  • Minerals Engineering
  • Statistics and Computing
  • Communication in Statistics- Theory and Methods
  • Computational Statistics & Data Analysis

Recent papers authored or coauthored by the scientist illustrate the range and focus of their research:

  • Approximation by finite mixtures of continuous density functions that vanish at infinity (2020, Cogent Mathematics & Statistics)
  • A new algorithm for support vector regression with automatic selection of hyperparameters (2022, Pattern Recognition)
  • Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopy (2021, Minerals Engineering)
  • Mini-batch learning of exponential family finite mixture models (2020, Statistics and Computing)
  • An overview of skew distributions in model-based clustering (2021, Journal of Multivariate Analysis)

Collaboration is a significant aspect of Geoffrey J. McLachlan's research activity, working frequently with several coauthors including:

  • Daniel Ahfock
  • Hien D. Nguyen
  • Faïcel Chamroukhi
  • Sharon Lee
  • TrungTin Nguyen

Geoffrey J. McLachlan has been recognized as a Fellow of the American Statistical Association (ASA) since 1998, which marks a noted point in their professional career.

Best Publications

  • Finite Mixture Models

    Geoffrey McLachlan;David Peel

  • The EM algorithm and extensions

    Geoffrey J. McLachlan;Thriyambakam Krishnan

  • Top 10 algorithms in data mining

    Xindong Wu;Vipin Kumar;J. Ross Quinlan;Joydeep Ghosh

  • Finite mixture models: McLachlan/finite mixture models

    Geoffrey McLachlan;David Peel

  • Discriminant Analysis and Statistical Pattern Recognition

    Geoffrey John McLachlan

  • Mixture models : inference and applications to clustering

    Geoffrey J. McLachlan;Kaye E. Basford

  • Selection bias in gene extraction on the basis of microarray gene-expression data.

    Christophe Ambroise;Geoffrey J. McLachlan

  • Modelling Survival Data in Medical Research.

    G. J. McLachlan;D. Collett

  • The EM Algorithm and Extensions: Second Edition

    Geoffrey J. McLachlan;Thriyambakam Krishnan

  • Robust mixture modelling using the t distribution

    D. Peel;G. J. McLachlan

  • On Bootstrapping the Likelihood Ratio Test Statistic for the Number of Components in a Normal Mixture

    G. J. McLachlan

  • Analyzing Microarray Gene Expression Data

    Geoffrey J. McLachlan;Kim-Anh Do;Christophe Ambroise

  • A mixture model-based approach to the clustering of microarray expression data

    Geoffrey J. McLachlan;Richard Bean;David Peel

  • Discriminant Analysis and Statistical Pattern Recognition: McLachlan/Discriminant Analysis & Pattern Recog

    Unknown

  • On Bayesian analysis of mixtures with an unknown number of components. Discussion. Author's reply

    S. Richardson;P. J. Green;C. P. Robert;M. Aitkin

  • Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages

    Kate Schroder;Katharine M Irvine;Martin S Taylor;Nilesh J Bokil

  • Modelling high-dimensional data by mixtures of factor analyzers

    G. J. McLachlan;D. Peel;R. W. Bean

  • Automated high-dimensional flow cytometric data analysis

    Saumyadipta Pyne;Xinli Hu;Kui Wang;Elizabeth Rossin

  • Mixtures of Factor Analyzers

    Geoffrey J. McLachlan;David Peel

  • Mixture Models: Inference and Applications to Clustering.

    Bruce Lindsay;G. L. McLachlan;K. E. Basford;Marcel Dekker

  • Comprehensive chemometrics: chemical and biochemical data analysis

    G. J. McLachlan;S. Rathnayake;S. X. Lee

  • Clustering objects on subsets of attributes

    DJ Hand;C Glasbey;D Husmeier;JC Gower

Frequent Co-Authors

Kim Anh Do
Kim Anh Do The University of Texas MD Anderson Cancer Center
John J. McGrath
John J. McGrath Aarhus University
Dianhui Wang
Dianhui Wang La Trobe University
David A. Hafler
David A. Hafler Yale University
Jill P. Mesirov
Jill P. Mesirov University of California, San Diego
Pablo Tamayo
Pablo Tamayo University of California, San Diego
Jason P. Lerch
Jason P. Lerch Hospital for Sick Children
David J. Hand
David J. Hand Imperial College London
David C. Reutens
David C. Reutens University of Queensland
Suzanne K. Chambers
Suzanne K. Chambers University of Technology Sydney

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