World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6768
World Ranking
8876
National Ranking
535

Alun Preece 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 Alun Preece 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: 302 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Alun Preece 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 Alun Preece 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Alun Preece is affiliated with Cardiff University in the United Kingdom and has contributed extensively to the field of computer science, with a particular focus on artificial intelligence and its applications in social media and communications.

The primary areas of study for Alun Preece include:

  • Artificial Intelligence
  • Signal Processing
  • Sociology and Political Science
  • Computer Networks and Communications
  • Communication

Preece's research topics show a specialized interest in the intersection of AI and social behavior, covering themes such as:

  • Explainable Artificial Intelligence (XAI)
  • Topic Modeling
  • Social Media and Politics
  • Misinformation and Its Impacts
  • Time Series Analysis and Forecasting
  • Sentiment Analysis and Opinion Mining
  • Advanced Text Analysis Techniques

The scientist has published numerous papers in a variety of academic venues, including:

  • arXiv (Cornell University)
  • Online Social Networks and Media
  • Future Generation Computer Systems
  • Concurrency and Computation Practice and Experience
  • Patterns

Notable recent papers include:

  • Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI (2020, Patterns)
  • Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication (2023, Online Social Networks and Media)
  • Real-Time Text Classification of User-Generated Content on Social Media: Systematic Review (2021, IEEE Transactions on Computational Social Systems)
  • DeepProbCEP: A neuro-symbolic approach for complex event processing in adversarial settings (2022, Expert Systems with Applications)
  • Efficient orchestration of Node-RED IoT workflows using a Vector Symbolic Architecture (2020, Future Generation Computer Systems)

Frequent collaborators in research have included:

  • Federico Cerutti
  • Mani Srivastava
  • Marc Roig Vilamala
  • Lance Kaplan
  • José Camacho-Collados

Best Publications

  • Interpretability of deep learning models: A survey of results

    Supriyo Chakraborty;Richard Tomsett;Ramya Raghavendra;Daniel Harborne

  • Agent-based formation of virtual organisations

    Timothy J. Norman;Alun Preece;Stuart Chalmers;Nicholas R. Jennings

  • The KRAFT architecture for knowledge fusion and transformation

    A. Preece;K. Hui;A. Gray;P. Marti

  • AAMAS '05: Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

    Jigar Patel;W. T. Luke Teacy;Nicholas R. Jennings;Michael Luck

  • Foundation and application of knowledge base verification

    Alun D. Preece;Rajjan Shinghal

  • Agent-based virtual organisations for the Grid

    Jigar Patel;W. T. Luke Teacy;Nicholas R. Jennings;Michael Luck

  • Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges

    Alun David Preece

  • Better knowledge management through knowledge engineering

    A. Preece;A. Flett;D. Sleeman;D. Curry

  • Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI.

    Richard Tomsett;Alun D. Preece;Dave Braines;Federico Cerutti;Federico Cerutti

  • Towards a methodology for evaluating expert systems

    Alun D. Preece

  • KRAFT: knowledge fusion from distributed databases and knowledge bases

    P.M.D. Gray;A. Preece;N.J. Fiddian;W.A. Gray

  • An Ontology-Centric Approach to Sensor-Mission Assignment

    Mario Gomez;Alun Preece;Matthew P. Johnson;Geeth Mel

  • Interpretable to whom? A role-based model for analyzing interpretable machine learning systems

    Richard Tomsett;David Braines;Daniel Harborne;Alun David Preece

  • Principles and practice in verifying rule-based systems

    Alun D. Preece;Rajjan Shinghal;Aïda Batarekh

  • KRAFT: AN AGENT ARCHITECTURE FOR KNOWLEDGE FUSION

    Alun David Preece;Kit Hui;William Alexander Gray;Philippe Marti

  • Sanity checks for saliency metrics

    Richard Tomsett;Daniel Harborne;Supriyo Chakraborty;Prudhvi Gurram

  • Verifying expert systems: A logical framework and a practical tool

    Alun D. Preece;Rajjan Shinghal;Aïda Batarekh

  • The role of idioms in sentiment analysis

    Lowri Williams;Christian Bannister;Michael Arribas-Ayllon;Alun Preece

  • CONOISE: Agent-based formation of virtual organisations

    Timothy J. Norman;Alun D. Preece;Stuart W. Chalmers;Nicholas R. Jennings

  • Evaluating Verification and Validation Methods in Knowledge Engineering

    Alun Preece

  • Stakeholders in explainable AI

    Alun Preece;Daniel Harborne;David Braines;Richard Tomsett

Frequent Co-Authors

Timothy J. Norman
Timothy J. Norman University of Southampton
Ian Taylor
Ian Taylor University of Notre Dame
Michael Luck
Michael Luck University of Sussex
Mani Srivastava
Mani Srivastava University of California, Los Angeles
Lance Kaplan
Lance Kaplan United States Army Research Laboratory
Thomas F. La Porta
Thomas F. La Porta Pennsylvania State University
Nicholas R. Jennings
Nicholas R. Jennings Loughborough University
Amotz Bar-Noy
Amotz Bar-Noy City University of New York
Paolo Missier
Paolo Missier Newcastle University
Glyn Elwyn
Glyn Elwyn Dartmouth Institute for Health Policy and Clinical Practice

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