World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
34
Citations
11614
World Ranking
11887
National Ranking
589

Peter Fettke 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 Peter Fettke 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: 232 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.

Peter Fettke 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 Peter Fettke 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Peter Fettke is affiliated with the German Research Centre for Artificial Intelligence in Germany. Their research focuses primarily on computer science and business management, with significant contributions to areas such as management information systems, artificial intelligence, industrial and manufacturing engineering, information systems, and management science and operations research.

Their main topics of work include:

  • Business Process Modeling and Analysis
  • Service-Oriented Architecture and Web Services
  • Big Data and Business Intelligence
  • Explainable Artificial Intelligence (XAI)
  • Simulation Techniques and Applications
  • Data Quality and Management
  • Manufacturing Process and Optimization

Peter Fettke has authored multiple papers across diverse venues, with notable recent publications including:

  • "Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective," 2024, Annals of Operations Research
  • "A Multi-Sensor Approach for Digital Twins of Manual Assembly and Commissioning," 2020, Procedia Manufacturing
  • "Manufacturing execution systems driven process analytics: A case study from individual manufacturing," 2021, Procedia CIRP
  • "Deep learning-based clustering of processes and their visual exploration: An industry 4.0 use case for small, medium-sized enterprises," 2022, Expert Systems
  • "Local Post-Hoc Explanations for Predictive Process Monitoring in Manufacturing," 2020, arXiv (Cornell University)

Frequently publishing venues for Fettke's work include:

  • arXiv (Cornell University)
  • Proceedings of the Annual Hawaii International Conference on System Sciences
  • Universität des Saarlandes
  • DFKI GmbH, Institut für Wirtschaftsinformatik
  • KI - Künstliche Intelligenz

They have collaborated extensively with co-authors such as Wolfgang Reisig, Nijat Mehdiyev, Péter Pfeiffer, Maxim Majlatow, and Constantin Houy, reflecting ongoing partnerships in their fields of study.

In addition to articles, Peter Fettke has contributed to book publications, including a work published by Springer Science+Business Media titled "Business Process Management: Blockchain and Robotic Process Automation Forum" in 2021.

Best Publications

  • Industry 4.0

    Heiner Lasi;Peter Fettke;Hans-Georg Kemper;Thomas Feld

  • Business Process Modeling Notation

    Peter Fettke

  • Model Driven Architecture (MDA)

    Peter Fettke;Peter Loos

  • Predicting process behaviour using deep learning

    Joerg Evermann;Jana-Rebecca Rehse;Jana-Rebecca Rehse;Peter Fettke;Peter Fettke

  • State-of-the-Art des State-of-the-Art

    Peter Fettke

  • Classification of reference models: a methodology and its application

    Peter Fettke;Peter Loos

  • Empirical research in business process management – analysis of an emerging field of research

    Constantin Houy;Peter Fettke;Peter Loos

  • Business process reference models : Survey and classification

    Peter Fettke;Peter Loos;Jörg Zwicker

  • Business process reference models: survey and classification

    Peter Fettke;Peter Loos;Jörg Zwicker

  • Reference Modeling for Business Systems Analysis

    Peter Fettke;Peter Loos

  • How Conceptual Modeling Is Used

    Peter Fettke

  • ONTOLOGICAL EVALUATION OF REFERENCE MODELS USING THE BUNGE-WAND-WEBER MODEL

    Peter Fettke;Peter Loos

  • Time Series Classification using Deep Learning for Process Planning: A Case from the Process Industry

    Nijat Mehdiyev;Johannes Lahann;Andreas Emrich;David Lee Enke

  • A Deep Learning Approach for Predicting Process Behaviour at Runtime

    Joerg Evermann;Jana-Rebecca Rehse;Jana-Rebecca Rehse;Peter Fettke;Peter Fettke

  • Referenzmodellierungsforschung@@@Reference modeling research

    Peter Fettke;Peter Loos

  • A systematic literature review on state-of-the-art deep learning methods for process prediction

    Dominic A. Neu;Dominic A. Neu;Johannes Lahann;Johannes Lahann;Peter Fettke;Peter Fettke

  • Perspectives on Reference Modeling

    Peter Fettke;Peter Loos

  • Multiperspective evaluation of reference models: Towards a framework

    Peter Fettke;Peter Loos

  • Towards an Integrative Big Data Analysis Framework for Data-Driven Risk Management in Industry 4.0

    Tim Niesen;Constantin Houy;Peter Fettke;Peter Loos

  • Report : The Process Model Matching Contest 2013

    Ugur Cayoglu;Remco M. Dijkman;Marlon Dumas;Peter Fettke

  • Understanding understandability of conceptual models --- what are we actually talking about?

    Constantin Houy;Peter Fettke;Peter Loos

  • A Novel Business Process Prediction Model Using a Deep Learning Method

    Nijat Mehdiyev;Nijat Mehdiyev;Joerg Evermann;Peter Fettke;Peter Fettke

  • Evaluating Forecasting Methods by Considering Different Accuracy Measures

    Nijat Mehdiyev;Nijat Mehdiyev;David Lee Enke;Peter Fettke;Peter Fettke;Peter Loos;Peter Loos

Frequent Co-Authors

Jan vom Brocke
Jan vom Brocke University of Münster
Wil M. P. van der Aalst
Wil M. P. van der Aalst RWTH Aachen University
Ingo Weber
Ingo Weber Technical University of Berlin
John Krogstie
John Krogstie Norwegian University of Science and Technology
Matthias Weidlich
Matthias Weidlich Humboldt-Universität zu Berlin
Remco Dijkman
Remco Dijkman Eindhoven University of Technology
Jan Mendling
Jan Mendling Humboldt-Universität zu Berlin
Wolfgang Reisig
Wolfgang Reisig Humboldt-Universität zu Berlin
Alexander Maedche
Alexander Maedche Karlsruhe Institute of Technology
Martin Bichler
Martin Bichler Technical University of Munich

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