World's Best Scientists 2026 revealed!
Jan Beirlant

Jan Beirlant

D-Index & Metrics

Mathematics

D-Index
43
Citations
10381
World Ranking
1669
National Ranking
21

Jan Beirlant 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 Jan Beirlant 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: 197 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Jan Beirlant 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 Jan Beirlant 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: 43 D-Index — 54th percentile

54% of scientists in this discipline score the same or lower.

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

Overview

Jan Beirlant is affiliated with KU Leuven in Belgium and has contributed extensively to the fields of mathematics, economics, econometrics, and finance. Their research primarily focuses on statistics and probability, with significant contributions to financial risk and volatility modeling, as well as statistical distribution estimation and applications.

The scientist's work is distributed among multiple subfields including statistics and probability, finance, global and planetary change, artificial intelligence, and statistical methods involving uncertainty. Key topics covered in their research include financial risk and volatility modeling, hydrology and drought analysis, advanced statistical methods and models, statistical inference, probability and risk models, and Bayesian inference methods.

The publication record features recent papers such as:

  • GENERALIZING THE LOG-MOYAL DISTRIBUTION AND REGRESSION MODELS FOR HEAVY-TAILED LOSS DATA, 2020, Astin Bulletin
  • Fitting Nonstationary Cox Processes: An Application to Fire Insurance Data, 2020, North American Actuarial Journal
  • TEMPERED PARETO-TYPE MODELLING USING WEIBULL DISTRIBUTIONS, 2021, Astin Bulletin
  • Generalized Sum Plots, 2022, Lirias (KU Leuven)
  • A new class of copula regression models for modelling multivariate heavy-tailed data, 2022, Insurance Mathematics and Economics

The frequent co-authors collaborating with Jan Beirlant include Hansjörg Albrecher, Martin Bladt, Zhengxiao Li, Andréhette Verster, and José Carlos Araujo-Acuna.

Their publications appear repeatedly in notable venues such as DOAJ (Directory of Open Access Journals), Astin Bulletin, Insurance Mathematics and Economics, Lirias (KU Leuven), and Extremes.

Best Publications

  • Statistics of Extremes: Theory and Applications

    Jan Beirlant;Yuri Goegebeur;Johan Segers;JozefL Teugels

  • Nonparametric entropy estimation. An overview

    J. Beirlant;EJ Dudewicz;László Györfi;István Dénes

  • Tail Index Estimation and an Exponential Regression Model

    Jan Beirlant;Goedele Dierckx;Yuri Goegebeur;Gunther Matthys

  • Practical analysis of extreme values

    Jan Beirlant;Jozef L. Teugels;Petra Vynckier

  • Tail Index Estimation, Pareto Quantile Plots, and Regression Diagnostics

    Jan Beirlant;Petra Vynckier;Jozef L. Teugels

  • Excess functions and estimation of the extreme-value index

    Jan Beirlant;Petra Vynckier;Josef L. Teugels

  • Actuarial statistics with generalized linear mixed models

    Katrien Antonio;Jan Beirlant

  • ESTIMATING THE EXTREME VALUE INDEX AND HIGH QUANTILES WITH EXPONENTIAL REGRESSION MODELS

    G Matthys;Jan Beirlant

  • Reinsurance: Actuarial and Statistical Aspects

    Hansjörg Albrecher;Jan Beirlant;Jozef L. Teugels

  • On exponential representations of log-spacings of extreme order statistics

    J. Beirlant;G. Dierckx;A. Guillou;C. Staăricaă

  • Estimation of the extreme-value index and generalized quantile plots

    Jan Beirlant;Goedele Dierckx;A Guillou

  • A robust estimator for the tail index of Pareto-type distributions

    B. Vandewalle;J. Beirlant;A. Christmann;M. Hubert

  • Estimation of the extreme value index and extreme quantiles under random censoring

    Jan Beirlant;Armelle Guillou;Goedele Dierckx;Amélie Fils-Villetard

  • Modeling large claims in non-life insurance

    Jan Beirlant;Jozef L. Teugels

  • HEAVY-TAILED DISTRIBUTIONS AND RATING

    J. Beirlant;G. Matthys;G. Dierckx

  • Estimating catastrophic quantile levels for heavy-tailed distributions

    Gunther Matthys;Emmanuel Delafosse;Armelle Guillou;Jan Beirlant

  • Kernel estimators for the second order parameter in extreme value statistics

    Yuri Goegebeur;Jan Beirlant;Tertius de Wet

  • Local polynomial maximum likelihood estimation for Pareto-type distributions

    Jan Beirlant;Yuri Goegebeur

  • Mean-of-order p reduced-bias extreme value index estimation under a third-order framework

    Frederico Caeiro;M. Ivette Gomes;Jan Beirlant;Jan Beirlant;Tertius de Wet

  • The mean residual life function at great age: Applications to tail estimation

    Jan Beirlant;Michel Broniatowski;Jozef L. Teugels;Petra Vynckier

  • Statistical Size Distributions in Economics and Actuarial Sciences

    Jan Beirlant

  • Universal smoothing factor selection in density estimation: theory and practice - Discussion

    Jan Beirlant

Frequent Co-Authors

Johan Segers
Johan Segers Université Catholique de Louvain
Hansjörg Albrecher
Hansjörg Albrecher University of Lausanne
László Györfi
László Györfi Budapest University of Technology and Economics
Mia Hubert
Mia Hubert KU Leuven
Jef Caers
Jef Caers Stanford University
Jan Dhaene
Jan Dhaene KU Leuven
Wim Schoutens
Wim Schoutens KU Leuven
Luc Devroye
Luc Devroye McGill University
Andrzej Kijko
Andrzej Kijko University of Pretoria

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