World's Best Scientists 2026 revealed!
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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
69
Citations
24315
World Ranking
1941
National Ranking
75

Eyke Hüllermeier 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 Eyke Hüllermeier 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 526 publications — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Eyke Hüllermeier 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 Eyke Hüllermeier sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 69 D-Index — 87th percentile

87% 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

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Eyke Hüllermeier is affiliated with Ludwig-Maximilians-Universität München in Germany. Their research primarily lies within the broad field of Computer Science, with a significant focus on subfields such as Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Computer Vision and Pattern Recognition, and Computational Theory and Mathematics.

The scientist's key research topics cover various areas in machine learning and artificial intelligence. These include:

  • Machine Learning and Data Classification
  • Machine Learning and Algorithms
  • Explainable Artificial Intelligence (XAI)
  • Bayesian Modeling and Causal Inference
  • Advanced Bandit Algorithms Research
  • Text and Document Classification Technologies
  • Data Stream Mining Techniques

Eyke Hüllermeier has contributed to numerous research papers published in notable venues. Some recent papers include:

  • "ChatGPT for good? On opportunities and challenges of large language models for education" (2023) published in Learning and Individual Differences
  • "How to measure uncertainty in uncertainty sampling for active learning" (2021) published in Machine Learning
  • "AutoML for Multi-Label Classification: Overview and Empirical Evaluation" (2021) published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems" (2020) published in IEEE Transactions on Cognitive and Developmental Systems
  • "A Survey of Methods for Automated Algorithm Configuration" (2022) published in Journal of Artificial Intelligence Research

The scientist frequently collaborates with several co-authors, including Marcel Wever, Viktor Bengs, Alexander Tornede, Barbara Hammer, and Maximilian Muschalik.

Eyke Hüllermeier has published extensively in several academic venues, with the highest number of publications appearing in:

  • arXiv (Cornell University)
  • Machine Learning
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Open access LMU (Ludwid Maxmilian's Universitat Munchen)
  • International Journal of Approximate Reasoning

In addition to journal and conference publications, Eyke Hüllermeier has authored books published by Springer Science+Business Media and the Centre National de la Recherche Scientifique. Notable works include Discovery Science (2021) and Advances in Intelligent Data Analysis XX (2022) from Springer, as well as Actes de la conférence CAID 2020 (2021) published by CNRS.

Best Publications

  • ChatGPT for good? On opportunities and challenges of large language models for education

    Unknown

  • Aleatoric and epistemic uncertainty in machine learning : an introduction to concepts and methods

    Eyke Hüllermeier;Willem Waegeman

  • Multilabel classification via calibrated label ranking

    Johannes Fürnkranz;Eyke Hüllermeier;Eneldo Loza Mencía;Klaus Brinker

  • Preference Learning and Ranking by Pairwise Comparison

    Johannes Fürnkranz;Eyke Hüllermeier

  • Label ranking by learning pairwise preferences

    Eyke Hüllermeier;Johannes Fürnkranz;Weiwei Cheng;Klaus Brinker

  • FURIA: an algorithm for unordered fuzzy rule induction

    Jens Christian Hühn;Eyke Hüllermeier

  • An Approach to Modelling and Simulation of Uncertain Dynamical Systems

    Eyke Hüllermeier

  • On label dependence and loss minimization in multi-label classification

    Krzysztof Dembczyński;Willem Waegeman;Weiwei Cheng;Eyke Hüllermeier

  • Open challenges for data stream mining research

    Georg Krempl;Indre Žliobaite;Dariusz Brzeziński;Eyke Hüllermeier

  • Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons

    H. Bustince;M. Pagola;R. Mesiar;E. Hullermeier

  • Online clustering of parallel data streams

    Jürgen Beringer;Eyke Hüllermeier

  • Combining instance-based learning and logistic regression for multilabel classification

    Weiwei Cheng;Eyke Hüllermeier

  • Preference Learning

    Unknown

  • Pairwise preference learning and ranking

    Johannes Fürnkranz;Eyke Hüllermeier

  • Fuzzy methods in machine learning and data mining: Status and prospects

    Eyke Hüllermeier

  • A systematic approach to the assessment of fuzzy association rules

    Didier Dubois;Eyke Hüllermeier;Henri Prade

  • Preferences in AI: An overview

    Carmel Domshlak;Eyke Hüllermeier;Souhila Kaci;Henri Prade

  • ML-Plan: Automated machine learning via hierarchical planning

    Felix Mohr;Marcel Dominik Wever;Eyke Hüllermeier

  • Learning from ambiguously labeled examples

    Eyke Hüllermeier;Jürgen Beringer

  • Decision tree and instance-based learning for label ranking

    Weiwei Cheng;Jens Hühn;Eyke Hüllermeier

  • Dependent binary relevance models for multi-label classification

    Elena Montañes;Robin Senge;Jose Barranquero;José Ramón Quevedo

  • A Unified Model for Multilabel Classification and Ranking

    Klaus Brinker;Johannes Fürnkranz;Eyke Hüllermeier

Frequent Co-Authors

Johannes Fürnkranz
Johannes Fürnkranz Johannes Kepler University of Linz
Didier Dubois
Didier Dubois Paul Sabatier University
Henri Prade
Henri Prade Paul Sabatier University
Frank Hoffmann
Frank Hoffmann TU Dortmund University
Rudolf Kruse
Rudolf Kruse Otto-von-Guericke University Magdeburg
Inés Couso
Inés Couso University of Oviedo
Toon Calders
Toon Calders University of Antwerp
Floriana Esposito
Floriana Esposito University of Bari Aldo Moro
Ralf Mikut
Ralf Mikut Karlsruhe Institute of Technology
Bernard De Baets
Bernard De Baets Ghent University

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