World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
17518
World Ranking
2735
National Ranking
1362

Jude W. Shavlik 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 Jude W. Shavlik 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: 233 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Jude W. Shavlik 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 Jude W. Shavlik 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: 63 D-Index — 81st percentile

81% 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

  • 2006 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to machine learning, especially knowledge-intensive approaches, and the application of machine learning to problems in computational biology.

Overview

Jude W. Shavlik is affiliated with the University of Wisconsin-Madison in the United States. Their work focuses on fields related to artificial intelligence and machine learning, with particular attention to knowledge-intensive approaches within these domains.

In recognition of their contributions, they were named a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2006. The award citation highlights their work on significant contributions to machine learning and the application of these methods to problems in computational biology.

Jude W. Shavlik's research includes the intersection of machine learning techniques and biological data analysis. This multidisciplinary approach involves leveraging computational methods to address challenges in biology.

Best Publications

  • Extracting Refined Rules from Knowledge-Based Neural Networks

    Geoffrey G. Towell;Jude W. Shavlik

  • Knowledge-based artificial neural networks

    Geoffrey G. Towell;Jude W. Shavlik

  • Chapter 11 Transfer Learning

    Unknown

  • Extracting Tree-Structured Representations of Trained Networks

    Mark Craven;Jude W. Shavlik

  • Refinement of approximate domain theories by knowledge-based neural networks

    Geoffrey G. Towell;Jude W. Shavlik;Michiel O. Noordewier

  • Readings in Machine Learning

    Jude W. Shavlik;Thomas E. Deitterich;Thomas Dietterich

  • Symbolic and neural learning algorithms: an experimental comparison

    Jude W. Shavlik;Raymond J. Mooney;Geoffrey G. Towell

  • Actively Searching for an Effective Neural Network Ensemble

    David W Opitz;Jude W Shavlik

  • Using sampling and queries to extract rules from trained neural networks

    Mark Craven;Jude W. Shavlik

  • Creating advice-taking reinforcement learners

    Richard Maclin;Jude W. Shavlik

  • Generating Accurate and Diverse Members of a Neural-Network Ensemble

    David W. Opitz;Jude W. Shavlik

  • Using neural networks for data mining

    Mark W. Craven;Jude W. Shavlik

  • Extracting comprehensible models from trained neural networks

    Mark William Craven;Jude W. Shavlik

  • Extracting refined rules from knowledge-based neural networks

    Unknown

  • Learning users' interests by unobtrusively observing their normal behavior

    Jeremy Goecks;Jude Shavlik

  • Corleone: hands-off crowdsourcing for entity matching

    Chaitanya Gokhale;Sanjib Das;AnHai Doan;Jeffrey F. Naughton

  • THE EXTRACTION OF REFINED RULES FROM KNOWLEDGE BASED NEURAL NETWORKS

    G Towell;J Shavlik

  • Tuffy: scaling up statistical inference in Markov logic networks using an RDBMS

    Feng Niu;Christopher Ré;AnHai Doan;Jude Shavlik

  • Knowledge-Based Support Vector Machine Classifiers

    Glenn M. Fung;Olvi L. Mangasarian;Jude W. Shavlik

  • DeepDive: Web-scale Knowledge-base Construction using Statistical Learning and Inference

    Feng Niu;Ce Zhang;Christopher R;Jude Shavlik

  • Training Knowledge-Based Neural Networks to Recognize Genes in DNA Sequences

    Michiel O. Noordewier;Geoffrey G. Towell;Jude W. Shavlik

  • Training Knowledge-Based Neural Networks to Recognize Genes.

    Michiel O. Noordewier;Geoffrey G. Towell;Jude W. Shavlik

Frequent Co-Authors

Kristian Kersting
Kristian Kersting Technical University of Darmstadt
Mark Craven
Mark Craven University of Wisconsin–Madison
Frank DiMaio
Frank DiMaio University of Washington
Christopher Ré
Christopher Ré Stanford University
George N. Phillips
George N. Phillips Rice University
Ce Zhang
Ce Zhang ETH Zurich
Prasad Tadepalli
Prasad Tadepalli Oregon State University
Tina Eliassi-Rad
Tina Eliassi-Rad Northeastern University
Frederick R. Blattner
Frederick R. Blattner University of Wisconsin–Madison

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 in the USA opens doors to a wide range of online degrees and career options. Many students look for flexible pathways that balance cost, duration, and future earning potential. For instance, the cheapest 1 year online mba programs offer quick, business-oriented credentials that can complement a technical background and fast-track you into management roles.

If you're seeking specialized knowledge, there are 1 year masters programs available online in various fields, including computer science and data analytics. These options let you enhance your expertise and career prospects in a shorter timeframe.

For those prioritizing speed and affordability, consider enrolling in the fastest online degree programs. These programs are designed for students who want to enter the workforce quickly in high-demand industries, often leading to well-paying jobs.

With the growth of AI, pursuing the ai degrees that are most affordable online can help you specialize in emerging technologies. A focused AI education can position you for dynamic, future-proof careers in technology and beyond.

Best Scientists Citing Jude W. Shavlik

Trending Scientists