World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
70
Citations
30013
World Ranking
268
National Ranking
16

Gareth O. Roberts 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 Gareth O. Roberts 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: 82 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: 250 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Gareth O. Roberts 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 Gareth O. Roberts 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: 137 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: 70 D-Index — 93rd percentile

93% 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

  • 2013 - Fellow of the Royal Society, United Kingdom

Overview

Gareth O. Roberts is affiliated with the University of Warwick in the United Kingdom. Their research spans across the disciplines of mathematics and computer science, with a particular focus on statistics and probability as well as artificial intelligence. The work also extends into specialized areas such as mathematical physics, epidemiology, and finance.

The primary topics of their research include:

  • Markov Chains and Monte Carlo Methods
  • Bayesian Methods and Mixture Models
  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Gaussian Processes and Bayesian Inference
  • Stochastic processes and statistical mechanics
  • COVID-19 epidemiological studies

Their publication record shows consistent contributions to several academic venues, most frequently to arXiv (Cornell University), Journal of the Royal Statistical Society Series B (Statistical Methodology), The Annals of Applied Probability, Methodology And Computing In Applied Probability, and Bernoulli.

Notable recent papers include:

  • Optimal scaling of random-walk metropolis algorithms on general target distributions, 2020, Stochastic Processes and their Applications
  • High-dimensional scaling limits of piecewise deterministic sampling algorithms, 2022, The Annals of Applied Probability
  • Dimension-Free Mixing for High-Dimensional Bayesian Variable Selection, 2022, Journal of the Royal Statistical Society Series B (Statistical Methodology)
  • Efficient real-time monitoring of an emerging influenza pandemic: How feasible?, 2020, The Annals of Applied Statistics
  • Regeneration-enriched Markov processes with application to Monte Carlo, 2021, The Annals of Applied Probability

Their frequent collaborators include Krzysztof Łatuszyński, Murray Pollock, Jeffrey S. Rosenthal, Dootika Vats, and Joris Bierkens.

Gareth O. Roberts was awarded the title of Fellow of the Royal Society, United Kingdom, in 2013.

Best Publications

  • Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods

    A. F. M. Smith;G. O. Roberts

  • Weak convergence and optimal scaling of random walk Metropolis algorithms

    G. O. Roberts;A. Gelman;W. R. Gilks

  • Optimal scaling for various Metropolis-Hastings algorithms

    Gareth O. Roberts;Jeffrey S. Rosenthal

  • Examples of Adaptive MCMC

    Gareth O. Roberts;Jeffrey S. Rosenthal

  • Exponential convergence of Langevin distributions and their discrete approximations

    Gareth O. Roberts;Richard L. Tweedie

  • The pseudo-marginal approach for efficient Monte Carlo computations

    Christophe Andrieu;Gareth O. Roberts

  • General state space Markov chains and MCMC algorithms

    Gareth O. Roberts;Jeffrey S. Rosenthal

  • Optimal scaling of discrete approximations to Langevin diffusions

    Gareth O. Roberts;Jeffrey S. Rosenthal

  • MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster

    Simon L. Cotter;Gareth O. Roberts;A. M. Stuart;David White

  • Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler

    G. O. Roberts;S. K. Sahu

  • Networks and the epidemiology of infectious disease.

    Leon Danon;Ashley P. Ford;Thomas A. House;Chris P. Jewell

  • Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms

    G. O. Roberts;R. L. Tweedie

  • Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms

    G.O. Roberts;A.F.M. Smith

  • COUPLING AND ERGODICITY OF ADAPTIVE MARKOV CHAIN MONTE CARLO ALGORITHMS

    Gareth O. Roberts;Jeffrey S. Rosenthal

  • Convergence assessment techniques for Markov chain Monte Carlo

    Stephen P. Brooks;Gareth O. Roberts

  • Bayesian inference for partially observed stochastic epidemics

    P. D. O’Neill;G. O. Roberts

  • Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion)

    Alexandros Beskos;Omiros Papaspiliopoulos;Gareth O. Roberts;Paul Fearnhead

  • Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models

    Omiros Papaspiliopoulos;Gareth O. Roberts

  • Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions

    S. P. Brooks;P. Giudici;G. O. Roberts

  • Link analysis ranking: algorithms, theory, and experiments

    Allan Borodin;Gareth O. Roberts;Jeffrey S. Rosenthal;Panayiotis Tsaparas

Frequent Co-Authors

Jeffrey S. Rosenthal
Jeffrey S. Rosenthal University of Toronto
Andrew M. Stuart
Andrew M. Stuart California Institute of Technology
Paul Fearnhead
Paul Fearnhead Lancaster University
Walter R. Gilks
Walter R. Gilks University of Leeds
Richard L. Tweedie
Richard L. Tweedie University of Minnesota
Nicholas G. Polson
Nicholas G. Polson University of Chicago
Jesper Møller
Jesper Møller Aalborg University
Allan Borodin
Allan Borodin University of Toronto
Christian Franzke
Christian Franzke Universität Hamburg
Richard Pebody
Richard Pebody Public Health England

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Related Online Degrees & Career Pathways

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