World's Best Scientists 2026 revealed!
Barbara Hammer

Barbara Hammer

D-Index & Metrics

Computer Science

D-Index
47
Citations
10398
World Ranking
6425
National Ranking
301

Barbara Hammer 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 Barbara Hammer 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: 492 publications — 93rd percentile

93% of scientists in this discipline score the same or lower.

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

Barbara Hammer 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 Barbara Hammer 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Barbara Hammer is affiliated with Bielefeld University in Germany and has contributed extensively to the field of computer science, particularly focusing on artificial intelligence and related subfields.

Their research output includes 276 publications, with a significant emphasis on artificial intelligence, accumulating 215 works in this subfield. Other areas of interest include computer vision and pattern recognition, management science and operations research, civil and structural engineering, and signal processing.

Barbara Hammer's main topics of work cover a range of specialized areas such as:

  • Data Stream Mining Techniques
  • Anomaly Detection Techniques and Applications
  • Machine Learning and Data Classification
  • Explainable Artificial Intelligence (XAI)
  • Water Systems and Optimization
  • Advanced Bandit Algorithms Research
  • Adversarial Robustness in Machine Learning

Their recent papers demonstrate a focus on explainability, concept drift, and robust learning in evolving environments. Notable recent publications include:

  • "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
  • "Model-based explanations of concept drift" (2023), published in Neurocomputing
  • "One or two things we know about concept drift-a survey on monitoring in evolving environments. Part A: detecting concept drift" (2024), published in Frontiers in Artificial Intelligence
  • "Incremental permutation feature importance (iPFI): towards online explanations on data streams" (2023), published in Machine Learning
  • "Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning" (2021), published in Neural Networks

Barbara Hammer has frequently collaborated with several coauthors throughout their career. The most recurrent collaborators are:

  • André Artelt
  • Fabian Hinder
  • Valerie Vaquet
  • Eyke Hüllermeier
  • Johannes Brinkrolf

With publications appearing frequently in venues such as arXiv (Cornell University), Neurocomputing, the IEEE Symposium Series on Computational Intelligence (SSCI), ESANN proceedings, and Zenodo (CERN European Organization for Nuclear Research), Barbara Hammer has established a broad presence across multiple reputable conferences and journals.

In addition to journal and conference papers, Barbara Hammer has contributed to book publications, notably with Springer Science+Business Media, including titles in the "Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track" series in 2021.

Best Publications

  • Generalized relevance learning vector quantization

    Barbara Hammer;Thomas Villmann

  • Adaptive relevance matrices in learning vector quantization

    Petra Schneider;Michael Biehl;Barbara Hammer

  • Incremental on-line learning: A review and comparison of state of the art algorithms

    Viktor Losing;Viktor Losing;Barbara Hammer;Heiko Wersing

  • Incremental learning algorithms and applications

    Alexander Gepperth;Barbara Hammer

  • Parametric nonlinear dimensionality reduction using kernel t-SNE

    Andrej Gisbrecht;Alexander Schulz;Barbara Hammer

  • KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift

    Viktor Losing;Barbara Hammer;Heiko Wersing

  • Neural maps in remote sensing image analysis

    Thomas Villmann;Erzsébet Merényi;Barbara Hammer

  • Supervised Neural Gas with General Similarity Measure

    Barbara Hammer;Marc Strickert;Thomas Villmann

  • Merge SOM for temporal data

    Marc Strickert;Barbara Hammer

  • Batch and median neural gas

    Marie Cottrell;Barbara Hammer;Alexander Hasenfuß;Thomas Villmann

  • On the approximation capability of recurrent neural networks

    Barbara Hammer

  • Prototype-based models in machine learning.

    Michael Biehl;Barbara Hammer;Thomas Villmann

  • Recursive self-organizing network models

    Barbara Hammer;Alessio Micheli;Alessandro Sperduti;Marc Strickert

  • Limited Rank Matrix Learning, discriminative dimension reduction and visualization

    Kerstin Bunte;Petra Schneider;Barbara Hammer;Frank-Michael Schleif

  • A Note on the Universal Approximation Capability of Support Vector Machines

    Barbara Hammer;Kai Gersmann

  • Distance learning in discriminative vector quantization

    Petra Schneider;Michael Biehl;Barbara Hammer

  • A general framework for unsupervised processing of structured data

    Barbara Hammer;Alessio Micheli;Alessandro Sperduti;Marc Strickert

  • Dynamics and Generalization Ability of LVQ Algorithms

    Michael Biehl;Anarta Ghosh;Barbara Hammer

  • A general framework for dimensionality-reducing data visualization mapping

    Kerstin Bunte;Michael Biehl;Barbara Hammer

  • Topographic mapping of large dissimilarity data sets

    Barbara Hammer;Alexander Hasenfuss

  • Neural Smithing --- Supervised Learning in Feedforward Artificial Neural Networks

    Barbara Hammer

Frequent Co-Authors

Thomas Villmann
Thomas Villmann Hochschule Mittweida
Alexander Schulz
Alexander Schulz University of Copenhagen
Alessio Micheli
Alessio Micheli University of Pisa
Alessandro Sperduti
Alessandro Sperduti University of Padua
Peter Tino
Peter Tino University of Birmingham
Michel Verleysen
Michel Verleysen Université Catholique de Louvain
Pascal Hitzler
Pascal Hitzler Kansas State University
Jochen J. Steil
Jochen J. Steil Technische Universität Braunschweig
Mario Botsch
Mario Botsch TU Dortmund University
Axel Wismüller
Axel Wismüller University of Rochester

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