World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
17873
World Ranking
3753
National Ranking
1095

William L. Oberkampf 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 William L. Oberkampf 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: 143 publications — 24th percentile

24% of scientists in this discipline score the same or lower.

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

William L. Oberkampf 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 William L. Oberkampf 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: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

William L. Oberkampf is affiliated with Sandia National Laboratories in the United States. Their research spans several fields, with a particular focus on Decision Sciences and Computer Science. The main topics of their work include Probabilistic and Robust Engineering Design, Simulation Techniques and Applications, Advanced Multi-Objective Optimization Algorithms, Model Reduction and Neural Networks, Systems Engineering Methodologies and Applications, Software Reliability and Analysis Research, and Modeling and Simulation Systems.

The subfields of their study include Management Science and Operations Research, Statistics, Probability and Uncertainty, Computational Theory and Mathematics, Statistical and Nonlinear Physics, and Control and Systems Engineering.

Several papers reflect their contributions to areas connected to model validation, verification, and uncertainty quantification. Recent publications include:

  • Assessment of Model Validation, Calibration, and Prediction Approaches in the Presence of Uncertainty, 2022, Journal of Verification Validation and Uncertainty Quantification
  • Model validation hierarchies for connecting system design to modeling and simulation capabilities, 2023, Progress in Aerospace Sciences
  • Exploitation of a Validation Hierarchy for Modeling and Simulation, 2023, AIAA SCITECH 2023 Forum
  • Closure on the Discussion of "Models, Uncertainty, and the Sandia V&V Challenge Problem" (Hazelrigg, G. A., and Klutke, G. A., ASME J. Verif. Valid. Uncert., 2020, 5(1), p. 015501), 2020, Journal of Verification Validation and Uncertainty Quantification
  • Reviewer's Recognition, 2021, Journal of Verification Validation and Uncertainty Quantification

William L. Oberkampf has frequently collaborated with several co-authors, including Christopher J. Roy, James M. Luckring, Scott Shaw, R. E. Graves, and Nolan W. Whiting.

Their research has been published predominantly in venues such as the Journal of Verification Validation and Uncertainty Quantification, Progress in Aerospace Sciences, and the AIAA SCITECH Forum.

In addition to articles, William L. Oberkampf has contributed to the book titled Verification, Validation, and Uncertainty Quantification in Scientific Computing, published by Cambridge University Press in 2025.

Best Publications

  • Verification and Validation in Scientific Computing

    William L. Oberkampf;Christopher J. Roy

  • Verification and Validation in Computational Fluid Dynamics

    William L. Oberkampf;Timothy G. Trucano

  • Verification and validation.

    Timothy Guy Trucano;William L Oberkampf;Martin. Pilch

  • Verification, Validation, and Predictive Capability in Computational Engineering and Physics

    William L Oberkampf;Timothy G Trucano;Charles Hirsch

  • Error and uncertainty in modeling and simulation

    William L. Oberkampf;Sharon M. DeLand;Brian M. Rutherford;Kathleen V. Diegert

  • Challenge problems: uncertainty in system response given uncertain parameters

    William L. Oberkampf;Jon C. Helton;Cliff A. Joslyn;Steven F. Wojtkiewicz

  • Measures of agreement between computation and experiment: validation metrics

    William L. Oberkampf;Matthew F. Barone

  • An exploration of alternative approaches to the representation of uncertainty in model predictions

    Jon C. Helton;Jay D. Johnson;William Oberkampf

  • Calibration, validation, and sensitivity analysis: What's what

    Timothy G. Trucano;Laura Painton Swiler;Takera Igusa;William Oberkampf

  • Model validation and predictive capability for the thermal challenge problem

    Scott Ferson;William L. Oberkampf;Lev Ginzburg

  • Alternative representations of epistemic uncertainty

    Jon C. Helton;William Oberkampf

  • Mathematical representation of uncertainty

    William Oberkampf;Jon Helton;Kari Sentz

  • Verification and validation benchmarks

    William Louis Oberkampf;Timothy Guy Trucano

  • Experimental uncertainty estimation and statistics for data having interval uncertainty.

    Kreinovich, Vladik (Applied Biomathematics, Setauket, New York);Oberkampf, William Louis (Applied Biomathematics, Setauket, New York);Ginzburg, Lev (Applied Biomathematics, Setauket, New York);Ferson, Scott (Applied Biomathematics, Setauket, New York)

  • Dependence in probabilistic modeling, Dempster-Shafer theory, and probability bounds analysis.

    William Louis Oberkampf;W. Troy Tucker;Jianzhong Zhang;Lev Ginzburg

  • Issues in Computational Fluid Dynamics Code Verification and Validation

    William L. Oberkampf;Frederick G. Blottner

  • Summary from the epistemic uncertainty workshop: consensus amid diversity

    Scott Ferson;Cliff A. Joslyn;Jon C. Helton;William L. Oberkampf

  • A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory

    J.C. Helton;J.D. Johnson;W.L. Oberkampf;C.B. Storlie

  • Representation of analysis results involving aleatory and epistemic uncertainty

    Jon C. Helton;Jay D. Johnson;William L. Oberkampf;Cédric J. Sallaberry

  • Experimental Methodology for Computational Fluid Dynamics Code Validation

    Daniel P. Aeschliman;William L. Oberkampf

  • An exploration of alternative approaches to the representation of uncertainty in model predictions.

    Jay Dean Johnson;William Louis Oberkampf;Jon Craig Helton

Frequent Co-Authors

Christopher J. Roy
Christopher J. Roy Virginia Tech
Jon C. Helton
Jon C. Helton Arizona State University
Holger Babinsky
Holger Babinsky University of Cambridge
Christopher L. Rumsey
Christopher L. Rumsey Langley Research Center
Vladik Kreinovich
Vladik Kreinovich The University of Texas at El Paso
Roger B. Nelsen
Roger B. Nelsen Lewis & Clark College

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