World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
22720
World Ranking
9012
National Ranking
3827

D. Richard Kuhn publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where D. Richard Kuhn sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 208 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

D. Richard Kuhn D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where D. Richard Kuhn sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

D. Richard Kuhn is affiliated with the National Institute of Standards and Technology in the United States. Their work primarily spans the field of Computer Science, with a focus on software and artificial intelligence subfields. The main research areas include software testing and debugging techniques, software reliability and analysis research, and software engineering research. Additional topics of interest cover explainable artificial intelligence (XAI), software system performance and reliability, IoT and edge/fog computing, and blockchain technology applications and security.

Their research outputs have appeared in several frequent publication venues such as:

  • Computer
  • IEEE Reliability Magazine
  • Empirical Software Engineering
  • Mathematics in Computer Science
  • Annals of Mathematics and Artificial Intelligence

Recent notable papers include:

  • How does combinatorial testing perform in the real world: an empirical study, 2020, Empirical Software Engineering
  • An exploration of combinatorial testing-based approaches to fault localization for explainable AI, 2021, Annals of Mathematics and Artificial Intelligence
  • CT-IoT: a combinatorial testing-based path selection framework for effective IoT testing, 2021, Empirical Software Engineering
  • The Path to a Consensus on Artificial Intelligence Assurance, 2022, Computer
  • Combinatorial Testing for Building Reliable Systems, 2024, IEEE Reliability Magazine

Frequent collaborators in their research include:

  • Raghu N. Kacker
  • M S Raunak
  • Yu Lei
  • Dimitris E. Simos
  • Laura Freeman

The work by D. Richard Kuhn is characterized by a strong emphasis on combinatorial testing and reliability in software systems. This is reflected in the recurring themes of software performance, fault localization in AI systems, and path selection strategies for IoT testing within their recent publications.

The blend of studies in software systems and artificial intelligence demonstrates an interdisciplinary approach, addressing challenges in assurance, explainability, and dependable computing across emerging technology domains.

Best Publications

  • Proposed NIST standard for role-based access control

    David F. Ferraiolo;Ravi Sandhu;Serban Gavrila;D. Richard Kuhn

  • Role-based access control

    David F. Ferraiolo;D. Richard Kuhn;Ramaswamy Chandramouli

  • The NIST model for role-based access control: towards a unified standard

    Ravi Sandhu;David Ferraiolo;Richard Kuhn

  • Role-Based Access Controls

    David F. Ferraiolo;D. Richard Kuhn

  • Guide to Attribute Based Access Control (ABAC) Definition and Considerations

    Vincent Hu;David Ferraiolo;Richard Kuhn;Adam Schnitzer

  • A role-based access control model and reference implementation within a corporate intranet

    David F. Ferraiolo;John F. Barkley;D. Richard Kuhn

  • Attribute-Based Access Control

    Vincent C. Hu;D. Richard Kuhn;David F. Ferraiolo

  • Adding Attributes to Role-Based Access Control

    D Richard Kuhn;Edward J Coyne;Timothy R Weil

  • Security Considerations for Voice Over IP Systems

    David R. Kuhn;Thomas J. Walsh;S G. Fries

  • IPOG-IPOG-D: efficient test generation for multi-way combinatorial testing

    Yu Lei;Raghu Kacker;D. Richard Kuhn;Vadim Okun

  • Introduction to Combinatorial Testing

    D. Richard Kuhn;Raghu N. Kacker;Yu Lei

  • FAILURE MODES IN MEDICAL DEVICE SOFTWARE: AN ANALYSIS OF 15 YEARS OF RECALL DATA

    Dolores R. Wallace;D. Richard Kuhn

  • Mutual exclusion of roles as a means of implementing separation of duty in role-based access control systems

    D. Richard Kuhn

  • Practical Combinatorial Testing

    David R. Kuhn;Raghu N. Kacker;Yu Lei

  • Fault classes and error detection capability of specification-based testing

    D. Richard Kuhn

  • Sources of Failure in the Public Switched Telephone Network

    Unknown

  • ACTS: A Combinatorial Test Generation Tool

    Linbin Yu;Yu Lei;Raghu N. Kacker;D. Richard Kuhn

  • Refining the In-Parameter-Order Strategy for Constructing Covering Arrays

    Michael A Forbes;Michael A Forbes;Jim Lawrence;Jim Lawrence;Yu Lei;Raghu N. Kacker

  • Role Based Access Control for the World Wide Web

    John Barkley;Anthony Cincotta;David Ferraiolo;Serban Gavrila

  • Role-Based Access Control (2nd ed.)

    David Ferraiolo;Richard Kuhn;Ramaswamy Chandramouli

  • Learning Internet-of-Things Security "Hands-On"

    Constantinos Kolias;Angelos Stavrou;Jeffrey Voas;Irena Bojanova

  • SP 800-142. Practical Combinatorial Testing

    D. Richard Kuhn;Raghu N. Kacker;Yu Lei

Frequent Co-Authors

Raghu N. Kacker
Raghu N. Kacker National Institute of Standards and Technology
Yu Lei
Yu Lei The University of Texas at Arlington
Jeffrey Voas
Jeffrey Voas National Institute of Standards and Technology
Tao Xie
Tao Xie Peking University
Ravi Sandhu
Ravi Sandhu The University of Texas at San Antonio
W. Eric Wong
W. Eric Wong The University of Texas at Dallas
Douglas C. Montgomery
Douglas C. Montgomery Arizona State University
Samee U. Khan
Samee U. Khan Mississippi State University
Charles J. Colbourn
Charles J. Colbourn Arizona State University
Angelos Stavrou
Angelos Stavrou Virginia Tech

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

Exploring Computer Science doesn't stop at traditional on-campus degrees. Today, students have access to an array of affordable online degree programs that bring flexibility and cost savings. These online options make it easier for students to fit learning around work, family, or other commitments.

Admission standards vary, and some online schools that accept low gpa give more students a chance to pursue a career in tech. Many institutions offer accelerated formats, including 1 year computer science degree online programs that fast-track your entry into the tech workforce.

Computer Science also opens doors to diverse career paths. For example, tech expertise can be applied to fields like environmental science. Want more options? Find out what can you do with an environmental science degree and how technology intersects with other disciplines.

Online learning is expanding opportunities for anyone passionate about tech, offering various pathways to success, regardless of background or previous academic performance.

Best Scientists Citing D. Richard Kuhn

Trending Scientists

Recently Published Articles