World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
47
Citations
11557
World Ranking
1246
National Ranking
556

Bruce G. Lindsay 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 Bruce G. Lindsay 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: 107 publications — 14th percentile

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

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

Bruce G. Lindsay 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 Bruce G. Lindsay 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: 47 D-Index — 66th percentile

66% 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

  • 2016 - Member of the National Academy of Engineering For the design and implementation of high-performance distributed and extensible database systems.
  • 1998 - Fellow of the American Statistical Association (ASA)
  • 1996 - Fellow of John Simon Guggenheim Memorial Foundation

Overview

Bruce G. Lindsay was a researcher affiliated with Pennsylvania State University in the United States. Their research spanned multiple domains within the broad field of Biochemistry, Genetics, and Molecular Biology, with a focus on Genetics and Artificial Intelligence as subfields.

The scientist's work primarily involved topics related to Bayesian Methods and Mixture Models, Genetic Diversity and Population Structure, as well as Genetic Associations and Epidemiology. These research themes were reflected in their publications and collaborations.

Among the recent papers published by Bruce G. Lindsay were:

  • The topography of multivariate normal mixtures, 2021, UNC Libraries
  • Markov chain composite likelihood and its application in genetic recombination model, 2023, Journal of Statistical Computation and Simulation

Frequent co-authors included Surajit Ray, Jianping Sun, and Grace Rhodes, indicating collaborative work often aligned with statistical methods in genetics and related computational modeling.

Publications appeared in recognized venues such as UNC Libraries and the Journal of Statistical Computation and Simulation, which are consistent with the scientific fields of genetic modeling and computational statistics.

Bruce G. Lindsay received several distinguished awards throughout their career, including being named a Member of the National Academy of Engineering in 2016 for contributions to high-performance distributed and extensible database systems. They were also a Fellow of the American Statistical Association in 1998 and a Fellow of the John Simon Guggenheim Memorial Foundation in 1996.

The body of work produced by Bruce G. Lindsay encompassed scientific inquiry at the intersection of genetics and computational methods, contributing to understanding genetic structures and improving statistical approaches within this domain.

Best Publications

  • Mixture models : theory, geometry, and applications

    Bruce G. Lindsay

  • Widespread genome duplications throughout the history of flowering plants

    Liying Cui;P. Kerr Wall;James H. Leebens-Mack;Bruce G. Lindsay

  • The Geometry of Mixture Likelihoods: A General Theory

    Bruce G. Lindsay

  • Efficiency versus robustness : the case for minimum Hellinger distance and related methods

    Bruce G. Lindsay

  • Improving generalised estimating equations using quadratic inference functions

    Annie Qu;Bruce G. Lindsay;Bing Li

  • Semiparametric Estimation in the Rasch Model and Related Exponential Response Models, Including a Simple Latent Class Model for Item Analysis

    Bruce Lindsay;Clifford C. Clogg;John Grego

  • The distribution of the likelihood ratio for mixtures of densities from the one-parameter exponential family

    Dankmar Böhning;Ekkehart Dietz;Rainer Schaub;Peter Schlattmann

  • The Geometry of Mixture Likelihoods, Part II: The Exponential Family

    Bruce G. Lindsay

  • A Nonparametric Statistical Approach to Clustering via Mode Identification

    Jia Li;Surajit Ray;Bruce G. Lindsay

  • Monotonicity of quadratic-approximation algorithms

    Dankmar Böhning;Bruce G. Lindsay

  • Minimum disparity estimation for continuous models: Efficiency, distributions and robustness

    Ayanendranath Basu;Bruce G. Lindsay

  • The topography of multivariate normal mixtures

    Surajit Ray;Bruce G. Lindsay

  • Mixture Models: Inference and Applications to Clustering.

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

  • Moment Matrices: Applications in Mixtures

    Bruce G. Lindsay

  • Computer-assisted analysis of mixtures (C.A.MAM): statistical algorithms.

    Dankmar Bohning;Peter Schlattmann;Bruce Lindsay

  • Conditional score functions: Some optimality results

    Bruce Lindsay

  • Weighted Likelihood Equations with Bootstrap Root Search

    Marianthi Markatou;Ayanendranath Basu;Bruce G. Lindsay

  • A Semiparametric Mixture Approach to Case-Control Studies with Errors in Covariables

    Kathryn Roeder;Raymond J. Carroll;Bruce G. Lindsay

  • Local Modal Regression.

    Weixin Yao;Bruce G. Lindsay;Runze Li

  • Residual diagnostics for mixture models

    Bruce G. Lindsay;Kathryn Roeder

  • A New Index of Fit Based on Mixture Methods for the Analysis of Contingency Tables

    Tamás Rudas;Clifford C. Clogg;Bruce G. Lindsay

Frequent Co-Authors

Kathryn Roeder
Kathryn Roeder Carnegie Mellon University
Dankmar Böhning
Dankmar Böhning University of Southampton
Claude W. dePamphilis
Claude W. dePamphilis Pennsylvania State University
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
David Siegmund
David Siegmund Stanford University
Jim Leebens-Mack
Jim Leebens-Mack University of Georgia
Pamela S. Soltis
Pamela S. Soltis University of Florida
Webb Miller
Webb Miller Pennsylvania State University
Hong Ma
Hong Ma Pennsylvania State University
Bernie Devlin
Bernie Devlin University of Pittsburgh

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 studying Mathematics in the USA, exploring related online degrees can open diverse career opportunities. Many professionals complement their math background with business knowledge by pursuing an online MBA with transfer credits accepted. This option allows students to leverage prior coursework and accelerate their path to earning an advanced business degree.

In addition, the growing field of data science offers exciting prospects through programs like an MS in data analytics. This degree equips math graduates with technical expertise to analyze large datasets and make data-driven decisions, increasing their marketability across industries.

For those seeking flexibility, several of the easiest MBA programs provide accessible entry points without sacrificing quality. These programs offer practical skills in leadership and management, perfect for mathematicians aiming to transition into corporate roles.

Furthermore, the easiest MBA programs available online balance convenience with comprehensive curricula, making them an appealing choice for working professionals.

Combining mathematics with business or data analytics credentials enhances career versatility and equips graduates to thrive in today’s competitive job market.

Best Scientists Citing Bruce G. Lindsay

Recently Published Articles