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Mathematics
Australia
2026

D-Index & Metrics

Mathematics

D-Index
62
Citations
24229
World Ranking
461
National Ranking
12

Matt P. Wand 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 Matt P. Wand 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: 203 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Matt P. Wand 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 Matt P. Wand 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: 62 D-Index — 87th percentile

87% 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
  • 2000 - Fellow of the American Statistical Association (ASA)

Overview

Matt P. Wand is affiliated with the University of Technology Sydney in Australia. Their research spans primarily the fields of Mathematics and Computer Science, with a focus on Statistics and Probability as a prominent subfield. Other areas of specialization include Artificial Intelligence, Computer Vision and Pattern Recognition, Environmental Engineering, and Management Science and Operations Research.

The scientist's main research topics cover various aspects of statistical methodology and Bayesian approaches. These topics include Statistical Methods and Inference, Statistical Methods and Bayesian Inference, Bayesian Methods and Mixture Models, Gaussian Processes and Bayesian Inference, Advanced Statistical Methods and Models, Bayesian Modeling and Causal Inference, and Generative Adversarial Networks and Image Synthesis.

Their recent scholarly contributions include:

  • Usable and Precise Asymptotics for Generalized Linear Mixed Model Analysis and Design (2021), published in Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Streamlined Variational Inference for Linear Mixed Models with Crossed Random Effects (2022), published in Journal of Computational and Graphical Statistics
  • Fast approximate inference for multivariate longitudinal data (2021), published in Biostatistics
  • Streamlined variational inference for higher level group-specific curve models (2020), published in Statistical Modelling
  • A variational inference framework for inverse problems (2024), published in Computational Statistics & Data Analysis

Frequent collaborators include Luca Maestrini, Aishwarya Bhaskaran, Marianne Menictas, Tui H. Nolan, and Virginia X. He.

The scientist's publications have appeared in a variety of venues, with multiple works in arXiv (Cornell University). Other frequent publication venues are the Australian & New Zealand Journal of Statistics, AStA Advances in Statistical Analysis, SSRN Electronic Journal, and the Journal of the Royal Statistical Society Series B (Statistical Methodology).

Matt P. Wand was awarded the status of Fellow of the American Statistical Association (ASA) in 2000.

Best Publications

  • Semiparametric Regression: Example Index

    David Ruppert;M. P. Wand;R. J. Carroll

  • Multivariate Locally Weighted Least Squares Regression

    D. Ruppert;M. P. Wand

  • An Effective Bandwidth Selector for Local Least Squares Regression

    D. Ruppert;S. J. Sheather;M. P. Wand

  • Generalized Partially Linear Single-Index Models

    R. J. Carroll;Jianqing Fan;Irène Gijbels;M. P. Wand

  • Exact Mean Integrated Squared Error

    J. S. Marron;M. P. Wand

  • Explaining Variational Approximations

    J. T. Ormerod;M. P. Wand

  • Local polynomial kernel regression for generalized linear models and quasi-likelihood functions

    Jianqing Fan;Nancy E. Heckman;M. P. Wand

  • Multivariate plug-in bandwidth selection

    M. P. Wand;Chris Jones

  • Geoadditive models

    Unknown

  • Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation

    M. P. Wand;M. C. Jones

  • Data-Based Choice of Histogram Bin Width

    M. P. Wand

  • Bayesian Analysis for Penalized Spline Regression Using WinBUGS

    Ciprian M. Crainiceanu;David Ruppert;Matthew P. Wand

  • Transformations in Density Estimation

    M. P. Wand;J. S. Marron;D. Ruppert

  • Smoothing and mixed models

    M. P. Wand

  • Generalized additive distributed lag models: quantifying mortality displacement

    A. Zanobetti;M. P. Wand;J. Schwartz;L. M. Ryan

  • Self-organization of bacterial biofilms is facilitated by extracellular DNA.

    Erin S. Gloag;Lynne Turnbull;Alan Huang;Pascal Vallotton

  • Local polynomial variance-function estimation

    David Ruppert;M. P. Wand;Ulla Holst;Ola Hössjer

  • Simple Marginally Noninformative Prior Distributions for Covariance Matrices

    Alan Huang;M. P. Wand

  • Semiparametric Estimation in Logistic Measurement Error Models

    R. J. Carroll;M. P. Wand

  • On semiparametric regression with O'Sullivan penalized splines

    M. P. Wand;J. T. Ormerod

  • Semiparametric regression during 2003–2007

    David Ruppert;M.P. Wand;Raymond J. Carroll

  • Semiparametric Regression: Preface

    David Ruppert;M. P. Wand;R. J. Carroll

Frequent Co-Authors

Raymond J. Carroll
Raymond J. Carroll Texas A&M University
David Ruppert
David Ruppert Cornell University
James Stephen Marron
James Stephen Marron University of North Carolina at Chapel Hill
Brent A. Coull
Brent A. Coull Harvard University
Russ Hauser
Russ Hauser Harvard University
David C. Christiani
David C. Christiani Harvard University
Robert A. Greenes
Robert A. Greenes Arizona State University
M. C. Jones
M. C. Jones The Open University
Matthew Roughan
Matthew Roughan University of Adelaide
John R. David
John R. David Harvard University

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