World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
67
Citations
51252
World Ranking
323
National Ranking
180

Bradley P. Carlin 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 Bradley P. Carlin 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: 226 publications — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Bradley P. Carlin 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 Bradley P. Carlin 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: 67 D-Index — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Overview

Bradley P. Carlin is affiliated with the University of Minnesota in the United States. Their research primarily spans the fields of Mathematics and Biochemistry, Genetics and Molecular Biology. Within these broad areas, their work focuses on subfields including Statistics and Probability, Genetics, Molecular Biology, Management Science and Operations Research, and Computational Theory and Mathematics.

The scientist's contributions are centered on several key topics, notably Statistical Methods in Clinical Trials, Neurogenetic and Muscular Disorders Research, Advanced Causal Inference Techniques, Statistical Methods and Inference, Statistical Methods and Bayesian Inference, Optimal Experimental Design Methods, and Hereditary Neurological Disorders.

Bradley P. Carlin has published multiple papers in various academic venues. Some of the recent papers include:

  • Intrathecal Gene Therapy for Giant Axonal Neuropathy (2024, New England Journal of Medicine)
  • Hierarchical Bayesian modelling of disease progression to inform clinical trial design in centronuclear myopathy (2021, Orphanet Journal of Rare Diseases)
  • Bayesian Complex Innovative Trial Designs (CIDs) and Their Use in Drug Development for Rare Disease (2022, The Journal of Clinical Pharmacology)
  • <b>credsubs</b>: Multiplicity-Adjusted Subset Identification (2020, Journal of Statistical Software)
  • Pharmacokinetic/pharmacodynamic data extrapolation models for improved pediatric efficacy and toxicity estimation, with application to secondary hyperparathyroidism (2020, Pharmaceutical Statistics)

The scientist frequently collaborates with a group of co-authors, with repeated partnerships involving Bruno Boulanger, Arnaud Monseur, Leen Thielemans, Chris Freitag, and Laurent Servais.

Bradley P. Carlin's publications have appeared in a range of journals, including:

  • Statistics in Medicine
  • UNC Libraries
  • New England Journal of Medicine
  • Orphanet Journal of Rare Diseases
  • The Journal of Clinical Pharmacology

Best Publications

  • Bayesian measures of model complexity and fit

    David Spiegelhalter;Nicola G. Best;Bradley P. Carlin;Angelika van der Linde

  • Hierarchical Modeling and Analysis for Spatial Data

    Sudipto Banerjee;Bradley P. Carlin;Alan E. Gelfand

  • Bayes and Empirical Bayes Methods for Data Analysis.

    T. Leonard;B. P. Carlin;T. A. Louis

  • Bayes and Empirical Bayes Methods for Data Analysis

    Bradley P. Carlin;Thomas A. Louis

  • Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review

    Mary Kathryn Cowles;Bradley P. Carlin

  • Bayesian Methods for Data Analysis

    Bradley P. Carlin;Thomas A. Louis

  • Bayesian Model Choice Via Markov Chain Monte Carlo Methods

    Bradley P. Carlin;Siddhartha Chib

  • A Monte Carlo Approach to Nonnormal and Nonlinear State-Space Modeling

    Bradley P. Carlin;Nicholas G. Polson;David S. Stoffer

  • Markov Chain Monte Carlo in Practice: A Roundtable Discussion

    Robert E. Kass;Bradley P. Carlin;Andrew Gelman;Radford M. Neal

  • Hierarchical Bayesian Analysis of Changepoint Problems

    Bradley P. Carlin;Alan E. Gelfand;Adrian F. M. Smith

  • Hierarchical Spatio-Temporal Mapping of Disease Rates

    Lance A. Waller;Bradley P. Carlin;Hong Xia;Alan E. Gelfand

  • The deviance information criterion: 12 years on

    David J. Spiegelhalter;Nicola G. Best;Bradley P. Carlin;Angelika van der Linde

  • Bayesian Adaptive Methods for Clinical Trials

    Unknown

  • Efficient parametrisations for normal linear mixed models

    Alan E. Gelfand;Sujit K. Sahu;Bradley P. Carlin

  • Separate and Joint Modeling of Longitudinal and Event Time Data Using Standard Computer Packages

    Xu Guo;Bradley P Carlin

  • Markov chain monte carlo methods for computing bayes factors: A comparative review

    Cong Han;Bradley P Carlin

  • Hierarchical Commensurate and Power Prior Models for Adaptive Incorporation of Historical Information in Clinical Trials

    Brian P. Hobbs;Bradley P. Carlin;Sumithra J. Mandrekar;Daniel J. Sargent

  • Effect of Dissemination of Evidence in Reducing Injuries from Falls

    Mary E. Tinetti;Dorothy I. Baker;Mary King;Margaret Gottschalk

  • Insurance status and access to urgent ambulatory care follow-up appointments.

    Brent R. Asplin;Karin V. Rhodes;Helen Levy;Nicole Lurie

  • Frailty modeling for spatially correlated survival data, with application to infant mortality in Minnesota.

    Sudipto Banerjee;Melanie M. Wall;Bradley P. Carlin

  • Generalized Hierarchical Multivariate CAR Models for Areal Data

    Xiaoping Jin;Bradley P. Carlin;Sudipto Banerjee

  • Bayes and Empirical Bayes Methods for Data Analysis, Second Edition

    Bradley Carlin;Thomas Louis

Frequent Co-Authors

Alan E. Gelfand
Alan E. Gelfand Duke University
Sudipto Banerjee
Sudipto Banerjee University of California, Los Angeles
Peter Müller
Peter Müller The University of Texas at Austin
Haitao Chu
Haitao Chu University of Minnesota
J. Jack Lee
J. Jack Lee The University of Texas MD Anderson Cancer Center
Traci L. Toomey
Traci L. Toomey University of Minnesota
Darin J. Erickson
Darin J. Erickson University of Minnesota
Andrew Gelman
Andrew Gelman Columbia University
Katherine P. Theall
Katherine P. Theall Tulane University

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