World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
8387
World Ranking
7555
National Ranking
3284

Joanne Bechta Dugan 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 Joanne Bechta Dugan 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: 153 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Joanne Bechta Dugan 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 Joanne Bechta Dugan 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Software
  • Operating system

Her primary scientific interests are in Fault tree analysis, Reliability engineering, Algorithm, Fault tolerance and Data structure. Her Fault tree analysis study combines topics in areas such as Reliability theory, Set, Binary decision diagram and Markov chain. Her work carried out in the field of Markov chain brings together such families of science as Fault model, Logic gate and Parallel computing, Parallel processing.

Her Reliability engineering research focuses on subjects like Markov model, which are linked to Hazard and Fault coverage. She works mostly in the field of Fault tolerance, limiting it down to topics relating to Redundancy and, in certain cases, Hypercube, as a part of the same area of interest. Her work is dedicated to discovering how Data structure, Boolean function are connected with Computational complexity theory and Maintenance engineering and other disciplines.

Her most cited work include:

  • Dynamic fault-tree models for fault-tolerant computer systems (582 citations)
  • A discrete-time Bayesian network reliability modeling and analysis framework (297 citations)
  • A modular approach for analyzing static and dynamic fault trees (175 citations)

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

The scientist’s investigation covers issues in Fault tree analysis, Reliability engineering, Fault tolerance, Algorithm and Software. Joanne Bechta Dugan has researched Fault tree analysis in several fields, including Data mining, Binary decision diagram, Markov chain, Markov model and Data structure. Her studies deal with areas such as Bayesian network, Expert system, Artificial intelligence, Event tree and Probabilistic risk assessment as well as Data mining.

Her study in the field of Dependability is also linked to topics like Reliability and Imperfect. Her Fault tolerance research is multidisciplinary, incorporating perspectives in Redundancy, Fault model and Fault detection and isolation. Joanne Bechta Dugan combines subjects such as Reliability theory and Fault coverage with her study of Algorithm.

She most often published in these fields:

  • Fault tree analysis (50.43%)
  • Reliability engineering (41.88%)
  • Fault tolerance (25.64%)

What were the highlights of her more recent work (between 2010-2019)?

  • Artificial intelligence (12.82%)
  • Fault tree analysis (50.43%)
  • Binary decision diagram (14.53%)

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

Her scientific interests lie mostly in Artificial intelligence, Fault tree analysis, Binary decision diagram, Human–computer interaction and Reliability engineering. Her study on Robot learning, Stochastic gradient descent, Convolutional neural network and Deep learning is often connected to Experiential learning as part of broader study in Artificial intelligence. In her study, which falls under the umbrella issue of Fault tree analysis, Fault tolerance is strongly linked to Algorithm.

Her Fault tolerance research incorporates themes from Mathematical optimization and Markov chain, Markov model. Joanne Bechta Dugan has included themes like Boolean function and Data structure in her Binary decision diagram study. Her Reliability engineering study incorporates themes from Computation and Component.

Between 2010 and 2019, her most popular works were:

  • Reliability Analysis of Nonrepairable Cold-Standby Systems Using Sequential Binary Decision Diagrams (89 citations)
  • Efficient analysis of multi-state k -out-of- n systems (48 citations)
  • Reliability analysis of warm standby systems using sequential BDD (41 citations)

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

  • Artificial intelligence
  • Operating system
  • Software

Her primary areas of investigation include Fault tree analysis, Binary decision diagram, Reliability engineering, Algorithm and Component. The study incorporates disciplines such as Computation, Boolean function and Data structure in addition to Binary decision diagram. Her Data structure research integrates issues from Redundancy and Maintenance engineering.

Her study brings together the fields of Fault tolerance and Algorithm. Her biological study spans a wide range of topics, including Mathematical optimization and Markov chain, Markov model. Joanne Bechta Dugan works mostly in the field of Component, limiting it down to topics relating to Failure mode and effects analysis and, in certain cases, Computational complexity theory and Benchmark.

Best Publications

  • Dynamic fault-tree models for fault-tolerant computer systems

    J.B. Dugan;S.J. Bavuso;M.A. Boyd

  • A discrete-time Bayesian network reliability modeling and analysis framework

    Hichem Boudali;Joanne Bechta Dugan

  • Coverage modeling for dependability analysis of fault-tolerant systems

    J.B. Dugan;K.S. Trivedi

  • Developing a low-cost high-quality software tool for dynamic fault-tree analysis

    J.B. Dugan;K.J. Sullivan;D. Coppit

  • A modular approach for analyzing static and dynamic fault trees

    R. Gulati;J.B. Dugan

  • Empirical Analysis of Software Fault Content and Fault Proneness Using Bayesian Methods

    G.J. Pai;J.B. Dugan

  • A continuous-time Bayesian network reliability modeling, and analysis framework

    H. Boudali;J.B. Dugan

  • Analysis of generalized phased-mission system reliability, performance, and sensitivity

    Liudong Xing;J.B. Dugan

  • The Galileo fault tree analysis tool

    K.J. Sullivan;J.B. Dugan;D. Coppit

  • The hybrid automated reliability predictor

    Joanne Bechta Dugan;Kishor S. Trivedi;Mark K. Smotherman;Robert M. Geist

  • Automatic synthesis of dynamic fault trees from UML system models

    G.J. Pai;J.B. Dugan

  • Automated analysis of phased-mission reliability

    J.B. Dugan

  • Fault trees and sequence dependencies

    J.B. Dugan;S.J. Bavuso;M.A. Boyd

  • Minimal cut set/sequence generation for dynamic fault trees

    Zhihua Tang;J.B. Dugan

  • A separable method for incorporating imperfect fault-coverage into combinatorial models

    S.V. Amari;J.B. Dugan;R.B. Misra

  • Fault trees and Markov models for reliability analysis of fault-tolerant digital systems

    Joanne Bechta Dugan;Salvatore J. Bavuso;Mark A. Boyd

  • Combining various solution techniques for dynamic fault tree analysis of computer systems

    R. Manian;J. Bechta Dugan;D. Coppit;K.J. Sullivan

  • Reliability Analysis of Nonrepairable Cold-Standby Systems Using Sequential Binary Decision Diagrams

    Liudong Xing;O. Tannous;J. B. Dugan

  • DIFtree: a software package for the analysis of dynamic fault tree models

    J.B. Dugan;B. Venkataraman;R. Gulati

  • Analysis of Typical Fault-Tolerant Architectures using HARP

    Salvatore J. Bavuso;Joanne Bechta Dugan;Kishor S. Trivedi;Elizabeth M. Rothmann

Frequent Co-Authors

Liudong Xing
Liudong Xing University of Massachusetts Dartmouth
Kevin Sullivan
Kevin Sullivan University of Virginia
Kishor S. Trivedi
Kishor S. Trivedi Duke University
Suprasad V. Amari
Suprasad V. Amari BAE Systems (United States)
Michael R. Lyu
Michael R. Lyu Chinese University of Hong Kong
John Andrews
John Andrews University of Nottingham
Malathi Veeraraghavan
Malathi Veeraraghavan University of Virginia

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