World's Best Scientists 2026 revealed!
Luc De Raedt

Luc De Raedt

D-Index & Metrics

Computer Science

D-Index
79
Citations
25235
World Ranking
1144
National Ranking
13

Luc De Raedt 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 Luc De Raedt 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: 641 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Luc De Raedt 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 Luc De Raedt 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: 79 D-Index — 92nd percentile

92% 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

  • 2019 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to learning and reasoning through the integration of logical and relational representations in machine learning and probabilistic models.

Overview

Luc De Raedt is affiliated with KU Leuven in Belgium and conducts research primarily in Computer Science, with a particular focus on Artificial Intelligence. Their academic output includes 186 publications in the field of Computer Science and 150 specifically related to Artificial Intelligence.

Their work covers a variety of subfields and topics, including:

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Computational Theory and Mathematics

  • Semantic Web and Ontologies
  • Bayesian Modeling and Causal Inference
  • Logic, Reasoning, and Knowledge
  • AI-based Problem Solving and Planning
  • Natural Language Processing Techniques
  • Topic Modeling
  • Constraint Satisfaction and Optimization

Their research has been featured in frequent publication venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Lirias (KU Leuven)
  • Artificial Intelligence
  • Theory and Practice of Logic Programming

Among recent papers by or involving Luc De Raedt are:

  • "COVID-19 in people with multiple sclerosis: A global data sharing initiative" (2020), published in Multiple Sclerosis Journal
  • "Comprehensive targeted next-generation sequencing approach in the molecular diagnosis of gastrointestinal stromal tumor" (2020), published in Genes Chromosomes and Cancer
  • "From statistical relational to neurosymbolic artificial intelligence: A survey" (2024), published in Artificial Intelligence
  • "Automating data science" (2022), published in Communications of the ACM
  • "DeepStochLog: Neural Stochastic Logic Programming" (2022), published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequent collaborators include:

  • Giuseppe Marra
  • Pedro Zuidberg Dos Martires
  • Robin Manhaeve
  • Angelika Kimmig
  • Samuel Kolb

Luc De Raedt was awarded the title of Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2019 for contributions to learning and reasoning through integrating logical and relational representations in machine learning and probabilistic models.

Best Publications

  • Inductive Logic Programming : Theory and Methods

    Stephen Muggleton;Luc de Raedt

  • Top-down induction of first-order logical decision trees

    Hendrik Blockeel;Luc De Raedt

  • ProbLog: a probabilistic prolog and its application in link discovery

    Luc De Raedt;Angelika Kimmig;Hannu Toivonen

  • Encyclopedia of Machine Learning and Data Mining

    Unknown

  • Logical and Relational Learning

    Luc De Raedt

  • Top-Down Induction of Clustering Trees

    Hendrik Blockeel;Luc De Raedt;Jan Ramon

  • Relational reinforcement learning

    Sašo Džeroski;Luc De Raedt;Kurt Driessens

  • Probabilistic inductive logic programming

    Luc De Raedt;Kristian Kersting

  • Clausal Discovery

    Luc De Raedt;Luc Dehaspe

  • Inference and learning in probabilistic logic programs using weighted Boolean formulas

    Daan Fierens;Guy Van den Broeck;Joris Renkens;Dimitar Sht. Shterionov

  • Interpreting Bayesian Logic Programs

    Kristian Kersting;Luc De Raedt;Stefan Kramer

  • Mining Association Rules in Multiple Relations

    Luc Dehaspe;Luc De Raedt

  • Data mining and machine learning techniques for the identification of mutagenicity inducing substructures and structure activity relationships of noncongeneric compounds.

    Christoph Helma;Tobias Cramer;Stefan Kramer;Luc De Raedt

  • Molecular feature mining in HIV data

    Stefan Kramer;Luc De Raedt;Christoph Helma

  • Interactive theory revision: an inductive logic programming approach

    Luc De Raedt

  • Statistical Relational Artificial Intelligence: Logic, Probability, and Computation

    Luc De Raedt;Kristian Kersting;Sriraam Natarajan

  • DeepProbLog: Neural Probabilistic Logic Programming

    Robin Manhaeve;Sebastijan Dumancic;Angelika Kimmig;Thomas Demeester

  • Machine Learning: ECML 2001

    Luc De Raedt;Peter Flach

  • Relational Reinforcement Learning

    Saso Dzeroski;Luc De Raedt;Hendrik Blockeel

  • Bayesian Logic Programs

    Kristian Kersting;Luc De Raedt

  • Multi instance neural networks

    Jan Ramon;Luc De Raedt

  • Probabilistic logic learning

    Luc De Raedt;Kristian Kersting

  • Proceedings of the 22nd international conference on Machine learning

    Saso Dzeroski;Luc De Raedt;Stefan Wrobel

Frequent Co-Authors

Kristian Kersting
Kristian Kersting Technical University of Darmstadt
Siegfried Nijssen
Siegfried Nijssen Université Catholique de Louvain
Guy Van den Broeck
Guy Van den Broeck University of California, Los Angeles
Paolo Frasconi
Paolo Frasconi University of Florence
Kathleen Marchal
Kathleen Marchal Ghent University
Stephen Muggleton
Stephen Muggleton Imperial College London
Jan Ramon
Jan Ramon French Institute for Research in Computer Science and Automation - INRIA

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