World's Best Scientists 2026 revealed!
Jack P. C. Kleijnen

Jack P. C. Kleijnen

Award Badge
Mathematics
Netherlands
2023

D-Index & Metrics

Engineering and Technology

D-Index
60
Citations
17507
World Ranking
2139
National Ranking
49

Jack P. C. Kleijnen publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Jack P. C. Kleijnen sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 297 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Jack P. C. Kleijnen D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Jack P. C. Kleijnen sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 60 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2023 - Research.com Mathematics in Netherlands Leader Award
  • 2022 - Research.com Mathematics in Netherlands Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Normal distribution
  • Artificial intelligence

Jack P. C. Kleijnen spends much of his time researching Kriging, Latin hypercube sampling, Mathematical optimization, Metamodeling and Design of experiments. Jack P. C. Kleijnen has researched Kriging in several fields, including Deterministic simulation, Linear regression, Algorithm, Global optimization and Interpolation. The concepts of his Latin hypercube sampling study are interwoven with issues in Discrete event simulation, Regression analysis, Polynomial regression and Statistic.

Jack P. C. Kleijnen combines subjects such as Estimator, Fractional factorial design and Response surface methodology with his study of Mathematical optimization. His studies in Metamodeling integrate themes in fields like Regression and Flexibility. His Design of experiments research is multidisciplinary, relying on both Verification and validation, Statistical theory, Polynomial and Management science.

His most cited work include:

  • Kriging metamodeling in simulation : A review (699 citations)
  • Statistical tools for simulation practitioners (547 citations)
  • State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments (538 citations)

What are the main themes of his work throughout his whole career to date?

Jack P. C. Kleijnen mainly investigates Mathematical optimization, Kriging, Statistics, Regression analysis and Monte Carlo method. His Mathematical optimization research incorporates themes from Design of experiments, Polynomial, Taguchi methods and Response surface methodology. His Design of experiments study combines topics in areas such as Algorithm and Statistical theory.

His Kriging study integrates concerns from other disciplines, such as Deterministic simulation, Latin hypercube sampling, Global optimization and Metamodeling. The Metamodeling study combines topics in areas such as Function and Data mining. His Regression analysis study also includes fields such as

  • Linear regression that connect with fields like Generalized least squares,
  • Sensitivity and related Uncertainty analysis.

He most often published in these fields:

  • Mathematical optimization (23.37%)
  • Kriging (23.17%)
  • Statistics (22.15%)

What were the highlights of his more recent work (between 2011-2021)?

  • Kriging (23.17%)
  • Gaussian process (12.80%)
  • Mathematical optimization (23.37%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Kriging, Gaussian process, Mathematical optimization, Monte Carlo method and Metamodeling. His Kriging research integrates issues from Deterministic simulation and Algorithm, Global optimization. His work deals with themes such as Computer experiment and Interpolation, which intersect with Algorithm.

His research in Mathematical optimization intersects with topics in Decision rule, Resampling, Bootstrapping and Response surface methodology. His study focuses on the intersection of Response surface methodology and fields such as Regression analysis with connections in the field of Cross-validation. Jack P. C. Kleijnen interconnects Design of experiments and Regression in the investigation of issues within Metamodeling.

Between 2011 and 2021, his most popular works were:

  • Regression and Kriging metamodels with their experimental designs in simulation: A review (129 citations)
  • Expected improvement in efficient global optimization through bootstrapped kriging (76 citations)
  • Robust Optimization in Simulation: Taguchi and Krige Combined (58 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Normal distribution
  • Artificial intelligence

The scientist’s investigation covers issues in Kriging, Gaussian process, Mathematical optimization, Metamodeling and Design of experiments. Kriging is a subfield of Statistics that Jack P. C. Kleijnen tackles. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Variogram and Robust control.

Many of his studies on Metamodeling apply to Regression as well. His Design of experiments research includes themes of Simple, Delta method, Constraint, Toy problem and Statistic. His research in Robustness focuses on subjects like Response surface methodology, which are connected to Latin hypercube sampling.

Best Publications

  • Kriging metamodeling in simulation : A review

    Jack P.C. Kleijnen

  • Design and Analysis of Simulation Experiments

    Jack P. C. Kleijnen

  • Verification and validation of simulation models

    Jack P.C. Kleijnen

  • Statistical tools for simulation practitioners

    Jack P C Kleijnen

  • A Methodology for Fitting and Validating Metamodels in Simulation

    Jack P.C. Kleijnen;Robert G. Sargent

  • State-of-the-Art Review: A User's Guide to the Brave New World of Designing Simulation Experiments

    Jack P. C. Kleijnen;Susan M. Sanchez;Thomas W. Lucas;Thomas M. Cioppa

  • Performance metrics in supply chain management

    J.P.C. Kleijnen;M.T. Smits

  • Statistical Techniques in Simulation

    J. R. Walters;Jack P. C. Kleijnen

  • Experimental Design for Sensitivity Analysis, Optimization and Validation of Simulation Models

    J.P.C. Kleijnen

  • An overview of the design and analysis of simulation experiments for sensitivity analysis

    Jack P.C. Kleijnen

  • Supply chain simulation tools and techniques: A survey

    J.P.C. Kleijnen

  • Simulation: A Statistical Perspective

    Jack P. C. Kleijnen;Willen van Groenendaal

  • Application-driven sequential designs for simulation experiments: Kriging metamodelling

    J P C Kleijnen;W C M van Beers

  • Searching for important factors in simulation models with many factors: Sequential bifurcation

    Bert Bettonvil;Jack P.C. Kleijnen

  • Regression and Kriging metamodels with their experimental designs in simulation: A review

    Jack P.C. Kleijnen

  • Kriging for interpolation in random simulation

    W C M van Beers;J P C Kleijnen

  • Validation of models: statistical techniques and data availability

    Jack P. C. Kleijnen

  • Kriging interpolation in simulation: a survey

    W.C.M. van Beers;J.P.C. Kleijnen

  • A User's Guide to the Brave New World of Designing Simulation Experiments

    J.P.C. Kleijnen;S.M. Sanchez;T.W. Lucas;T.M. Cioppa

  • Sensitivity analysis and related analyses: A review of some statistical techniques

    Jack P.C. Kleijnen

  • Statistical Techniques in Simulation

    Jack P. C. Kleijnen;G. Arthur Mithram

Frequent Co-Authors

Dick den Hertog
Dick den Hertog University of Amsterdam
Mirjam Nielen
Mirjam Nielen Utrecht University
Reuven Y. Rubinstein
Reuven Y. Rubinstein Technion – Israel Institute of Technology
Robert G. Sargent
Robert G. Sargent Syracuse University
Jon C. Helton
Jon C. Helton Arizona State University
Ruud B.M. Huirne
Ruud B.M. Huirne Wageningen University & Research
JC Jan Fransoo
JC Jan Fransoo Tilburg University
Özalp Özer
Özalp Özer Amazon (United States)

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