World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
86
Citations
60550
World Ranking
745
National Ranking
393

Padhraic Smyth 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 Padhraic Smyth 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: 379 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Padhraic Smyth 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 Padhraic Smyth 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: 86 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2013 - ACM Fellow For contributions to probabilistic and statistical approaches to data mining and machine learning.

Overview

Padhraic Smyth is affiliated with the University of California, Irvine in the United States. Their research primarily spans the field of Computer Science with a strong emphasis on Artificial Intelligence. Their work also extends into subfields such as Global and Planetary Change, Computer Vision and Pattern Recognition, Atmospheric Science, and Signal Processing.

The main topics addressed in their research include:

  • Anomaly Detection Techniques and Applications
  • Explainable Artificial Intelligence (XAI)
  • Machine Learning and Data Classification
  • Fire effects on ecosystems
  • Data Stream Mining Techniques
  • Adversarial Robustness in Machine Learning
  • Machine Learning and Algorithms

Padhraic Smyth has contributed to a number of recent papers, notable among them are:

  • "Mining Big Data in Education: Affordances and Challenges," 2020, published in Review of Research in Education
  • "Bayesian modeling of human-AI complementarity," 2022, Proceedings of the National Academy of Sciences
  • "The benefits and caveats of using clickstream data to understand student self-regulatory behaviors: opening the black box of learning processes," 2020, International Journal of Educational Technology in Higher Education
  • "California wildfire spread derived using VIIRS satellite observations and an object-based tracking system," 2022, Scientific Data
  • "What large language models know and what people think they know," 2025, Nature Machine Intelligence

The frequently collaborating co-authors of Smyth include:

  • Mark Steyvers
  • Efi Foufoula-Georgiou
  • James T. Randerson
  • Stephan Mandt
  • Gavin Kerrigan

Smyth's publications are often found in recognized venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Statistical Analysis and Data Mining The ASA Data Science Journal
  • Nature Communications
  • IEEE Transactions on Geoscience and Remote Sensing

In addition to journal articles, Smyth has published a book titled Advances in Knowledge Discovery and Data Mining under the Springer Science+Business Media publisher in 2021.

Their academic work has been recognized with the ACM Fellow award in 2013, granted for contributions to probabilistic and statistical approaches to data mining and machine learning.

Best Publications

  • From Data Mining to Knowledge Discovery in Databases

    Usama M. Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • Principles of Data Mining

    David J. Hand;Padhraic Smyth;Heikki Mannila

  • Principles of Data Mining

    David J. Hand;Heikki Mannila;Padhraic Smyth

  • The KDD process for extracting useful knowledge from volumes of data

    Usama Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • From data mining to knowledge discovery: an overview

    Usama M. Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • Knowledge discovery and data mining: towards a unifying framework

    Usama Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • The author-topic model for authors and documents

    Michal Rosen-Zvi;Thomas Griffiths;Mark Steyvers;Padhraic Smyth

  • Rule discovery from time series

    Gautam Das;King-Ip Lin;Heikki Mannila;Gopal Renganathan

  • Probabilistic author-topic models for information discovery

    Mark Steyvers;Padhraic Smyth;Michal Rosen-Zvi;Thomas Griffiths

  • Fast collapsed gibbs sampling for latent dirichlet allocation

    Ian Porteous;David Newman;Alexander Ihler;Arthur Asuncion

  • A Spectral Clustering Approach To Finding Communities in Graph.

    Scott White;Padhraic Smyth

  • On smoothing and inference for topic models

    Arthur Asuncion;Max Welling;Padhraic Smyth;Yee Whye Teh

  • Clustering Sequences with Hidden Markov Models

    Padhraic Smyth

  • Trajectory clustering with mixtures of regression models

    Scott Gaffney;Padhraic Smyth

  • Algorithms for estimating relative importance in networks

    Scott White;Padhraic Smyth

  • Distributed Algorithms for Topic Models

    David Newman;Arthur Asuncion;Padhraic Smyth;Max Welling

  • An information theoretic approach to rule induction from databases

    P. Smyth;R.M. Goodman

  • Modeling the Internet and the Web

    Pierre Baldi;Paolo Frasconi;Padhraic Smyth

  • Visualization of navigation patterns on a Web site using model-based clustering

    Igor Cadez;David Heckerman;Christopher Meek;Padhraic Smyth

  • Probabilistic Independence Networks for Hidden Markov Probability Models

    Padhraic Smyth;Padhraic Smyth;David Heckerman;Michael I. Jordan

  • The KDD process for extracting useful knowledge from volumes of data : Data mining and knowledge discovery in databases

    U. Fayyad;G. Piatetsky-Shapiro;P. Smyth

Frequent Co-Authors

Alexander T. Ihler
Alexander T. Ihler University of California, Irvine
Heikki Mannila
Heikki Mannila Aalto University
Mark Steyvers
Mark Steyvers University of California, Irvine
Max Welling
Max Welling University of Amsterdam
Andrew W. Robertson
Andrew W. Robertson Columbia University
Usama M. Fayyad
Usama M. Fayyad Open Insights
David J. Hand
David J. Hand Imperial College London
Pierre Baldi
Pierre Baldi University of California, Irvine
Michael Ghil
Michael Ghil École Normale Supérieure
Paolo Frasconi
Paolo Frasconi University of Florence

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