World's Best Scientists 2026 revealed!
Ingrid Van Keilegom

Ingrid Van Keilegom

D-Index & Metrics

Mathematics

D-Index
36
Citations
6507
World Ranking
2615
National Ranking
35

Ingrid Van Keilegom 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 Ingrid Van Keilegom 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: 315 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Ingrid Van Keilegom 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 Ingrid Van Keilegom 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: 36 D-Index — 29th percentile

29% 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 American Statistical Association (ASA)

Overview

Ingrid Van Keilegom is affiliated with KU Leuven in Belgium and specializes in the field of Mathematics, with a particular focus on Statistics and Probability. Their academic work spans a diverse range of themes within statistical methodology and inference.

The main research topics covered in their publications include:

  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Bayesian Methods and Mixture Models
  • Advanced Causal Inference Techniques
  • Advanced Statistical Methods and Models
  • Statistical Distribution Estimation and Applications
  • Statistical Methods in Clinical Trials

Their research output includes numerous papers published in notable academic venues. Frequent publication platforms consist of:

  • arXiv (Cornell University)
  • Electronic Journal of Statistics
  • The Annals of Statistics
  • Scandinavian Journal of Statistics
  • Biometrika

Some of the recent research papers produced by Ingrid Van Keilegom and collaborators are:

  • Review on ROC Curves in the Presence of Covariates, 2022, DOAJ (DOAJ: Directory of Open Access Journals)
  • Dependent censoring based on parametric copulas, 2022, Biometrika
  • Infectious diseases epidemiology, quantitative methodology, and clinical research in the midst of the COVID-19 pandemic: Perspective from a European country, 2020, Contemporary Clinical Trials
  • Two-step semiparametric empirical likelihood inference, 2020, The Annals of Statistics
  • Copula-based inference for bivariate survival data with left truncation and dependent censoring, 2022, Insurance Mathematics and Economics

Frequent co-authors contributing to their scholarly work include:

  • Jad Beyhum
  • Jean-Pierre Florens
  • Geert Molenberghs
  • Eni Musta
  • Ariel Alonso

Ingrid Van Keilegom was recognized as a Fellow of the American Statistical Association (ASA) in 2013, reflecting an established presence within the statistical community.

Best Publications

  • Estimation of semiparametric models when the criterion function is not smooth

    Xiaohong Chen;Oliver Linton;Ingrid Van Keilegom

  • Extending the Scope of Empirical Likelihood

    Nils Lid Hjort;Ian W. McKeague;Ingrid Van Keilegom

  • Non-parametric Estimation of the Residual Distribution

    Michael G. Akritas;Ingrid Van Keilegom

  • Bootstrapping the Poisson log-bilinear model for mortality forecasting

    Natacha Brouhns;Michel Denuit;Ingrid Van Keilegom

  • Bootstrap confidence bands for regression curves and their derivatives

    Gerda Claeskens;Ingrid Van Keilegom

  • A review on empirical likelihood methods for regression

    Song Xi Chen;Song Xi Chen;Ingrid Van Keilegom

  • Cure models in survival analysis

    Maïlis Amico;Ingrid Van Keilegom

  • Cure Models in Survival Analysis

    Maïlis Amico;Ingrid Van Keilegom

  • Estimation of Semiparametric Models When the Criterion Function is Not Smooth

    Xiaohong Chen;Oliver B. Linton;Ingrid Van Keilegom

  • Two-sample tests in functional data analysis starting from discrete data

    Peter Hall;Ingrid Van Keilegom

  • Regression when both response and predictor are functions

    F. Ferraty;I. Van Keilegom;P. Vieu

  • Transfer of tail information in censored regression models

    Ingrid Van Keilegom;Michaël G. Akritas

  • On the Validity of the Bootstrap in Non-Parametric Functional Regression

    Frederic Ferraty;Ingrid Van Keilegom;Philippe Vieu

  • Estimation and Bootstrap with Censored Data in Fixed Design Nonparametric Regression

    Ingrid Van Keilegom;Noël Veraverbeke

  • Estimation of a semiparametric transformation model

    Y. Oliver Linton;Stefan Sperlich;Ingrid Van Keilegom

  • Nonparametric Least Squares Methods for Stochastic Frontier Models

    Léopold Simar;Ingrid Van Keilegom;Valentin Zelenyuk

  • Estimating the error distribution in nonparametric multiple regression with applications to model testing

    Natalie Neumeyer;Ingrid Van Keilegom

  • Goodness-of-fit tests in parametric regression based on the estimation of the error distribution

    Ingrid Van Keilegom;Wenceslao González Manteiga;César Andrés Sánchez Sellero

  • A new test for the parametric form of the variance function in non‐parametric regression

    Holger Dette;Natalie Neumeyer;Ingrid Van Keilegom

  • Empirical likelihood tests for two-sample problems via nonparametric density estimation

    Riccardo Cao;Ingrid Van Keilegom

  • Empirical Likelihood for Non-Smooth Criterion Functions

    Elisa Maria Molanes Lopez;Ingrid Van Keilegom;Noël Veraverbeke

  • Testing for the equality of k regression curves

    Juan Carlos Pardo-Fernandez;Ingrid Van Keilegom;Wenceslao Gonzalez-Manteiga

Frequent Co-Authors

Song Xi Chen
Song Xi Chen Peking University
Wenceslao González-Manteiga
Wenceslao González-Manteiga University of Santiago de Compostela
Raymond J. Carroll
Raymond J. Carroll Texas A&M University
Léopold Simar
Léopold Simar Université Catholique de Louvain
Holger Dette
Holger Dette Ruhr University Bochum
Enno Mammen
Enno Mammen Heidelberg University
Jeffrey S. Racine
Jeffrey S. Racine McMaster University
Oliver Linton
Oliver Linton University of Cambridge
Michel Denuit
Michel Denuit Université Catholique de Louvain
Paul W. Wilson
Paul W. Wilson Clemson University

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