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D-Index & Metrics

Computer Science

D-Index
38
Citations
5369
World Ranking
10338
National Ranking
411

James Miller 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 James Miller 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: 188 publications — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

James Miller 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 James Miller 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

James Miller is affiliated with the University of Alberta in Canada and has published extensively in the field of Computer Science, with a focus on Artificial Intelligence, Computer Networks and Communications, Information Systems, Software, and Social Psychology. Their research spans a variety of interconnected domains within these disciplines.

Key topics of Miller's work include:

  • Machine Learning and Data Classification
  • Software System Performance and Reliability
  • Explainable Artificial Intelligence (XAI)
  • Network Security and Intrusion Detection
  • Software-Defined Networks and 5G
  • Web Data Mining and Analysis
  • Software Engineering Research

Recent publications by Miller cover several relevant issues in software systems and data science:

  • "ServiceAnomaly: An anomaly detection approach in microservices using distributed traces and profiling metrics" (2023) published in the Journal of Systems and Software
  • "Towards Efficient Fine-Tuning of Language Models With Organizational Data for Automated Software Review" (2024) published in IEEE Transactions on Software Engineering
  • "Asterisk" (2020) published in ACM/IMS Transactions on Data Science
  • "TabReformer: Unsupervised Representation Learning for Erroneous Data Detection" (2021) published in ACM/IMS Transactions on Data Science
  • "Interpretation of Structural Preservation in Low-Dimensional Embeddings" (2020) published in IEEE Transactions on Knowledge and Data Engineering

Miller frequently collaborates with several researchers, including:

  • Mona Nashaat
  • Aindrila Ghosh
  • Shaikh Quader
  • Saeedeh Sadat Sajjadi Ghaemmaghami
  • Mahsa Panahandeh

Major publication venues include:

  • ACM/IMS Transactions on Data Science
  • Journal of Web Engineering
  • Journal of Systems and Software
  • IEEE Transactions on Software Engineering
  • Research Square

Best Publications

  • Integration of DNA Barcoding Into An Ongoing Inventory of Complex Tropical Biodiversity

    Daniel H. Janzen;Winnie Hallwachs;Patrick Blandin;John M. Burns

  • Evaluating inheritance depth on the maintainability of object-oriented software

    John W. Daly;Andrew Brooks;James Miller;Marc Roper

  • Consumer trust in e-commerce web sites: A meta-study

    Patricia Beatty;Ian Reay;Scott Dick;James Miller

  • Applying meta-analytical procedures to software engineering experiments

    James Miller

  • Further Experiences with Scenarios and Checklists

    J. Miller;M. Wood;M. Roper

  • Comparing and combining software defect detection techniques: a replicated empirical study

    Murray Wood;Marc Roper;Andrew Brooks;James Miller

  • Detecting visually similar Web pages: Application to phishing detection

    Teh-Chung Chen;Scott Dick;James Miller

  • Multi-method research: an empirical investigation of object-oriented technology

    Murray Wood;John Daly;James Miller;Marc Roper

  • A prototype empirical evaluation of test driven development

    A. Geras;M. Smith;J. Miller

  • Automatic test data generation using genetic algorithm and program dependence graphs

    James Miller;Marek Reformat;Howard Zhang

  • Practical assessment of the models for identification of defect-prone classes in object-oriented commercial systems using design metrics

    Giancarlo Succi;Witold Pedrycz;Milorad Stefanovic;James Miller

  • Statistical power and its subcomponents — missing and misunderstood concepts in empirical software engineering research

    James Miller;John W. Daly;Murray Wood;Marc Roper

  • Empirical evaluation of optimization algorithms when used in goal-oriented automated test data generation techniques

    Man Xiao;Mohamed El-Attar;Marek Reformat;James Miller

  • Two-factor graphical password for text password and encryption key generation

    John Charles Gyorffy;James Miller

  • Centroidal Voronoi Tessellations- A New Approach to Random Testing

    A. Shahbazi;A. F. Tappenden;J. Miller

  • Replicating software engineering experiments: a poisoned chalice or the Holy Grail

    James Miller

  • A Novel Evolutionary Approach for Adaptive Random Testing

    A.F. Tappenden;J. Miller

  • Replication's role in software engineering

    Andy Brooks;Marc Roper;Murray Wood;John W. Daly

  • Can results from software engineering experiments be safely combined

    J. Miller

  • An empirical evaluation of defect detection techniques

    Marc Roper;Murray Wood;James Miller

Frequent Co-Authors

Marc Roper
Marc Roper University of Strathclyde
Mehrdad Hajibabaei
Mehrdad Hajibabaei University of Guelph
Ian J. Kitching
Ian J. Kitching Natural History Museum
Paul D. N. Hebert
Paul D. N. Hebert University of Guelph
Witold Pedrycz
Witold Pedrycz University of Alberta
Ettore Merlo
Ettore Merlo Polytechnique Montréal
Giancarlo Succi
Giancarlo Succi University of Bologna
Abram Hindle
Abram Hindle University of Alberta
Gregor von Bochmann
Gregor von Bochmann University of Ottawa
Winnie Hallwachs
Winnie Hallwachs University of Pennsylvania

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