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Computer Science
Poland
2026

D-Index & Metrics

Computer Science

D-Index
97
Citations
39337
World Ranking
424
National Ranking
2

Roman Słowiński 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 Roman Słowiński 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: 438 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Roman Słowiński 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 Roman Słowiński 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: 97 D-Index — 97th percentile

97% 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

  • 2026 - Research.com Computer Science in Poland Leader Award
  • 2025 - Research.com Computer Science in Poland Leader Award
  • 2023 - Research.com Computer Science in Poland Leader Award
  • 2022 - Research.com Computer Science in Poland Leader Award
  • 2019 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)
  • 2017 - IEEE Fellow For contributions to dominance-based rough set theory, robust ordinal regression and preference learning
  • 2013 - Polish Academy of Science
  • 2013 - Member of Academia Europaea
  • 2005 - Prize of the Foundation for Polish Science - Nagroda Fundacji na rzecz Nauki Polskiej for developing a methodology for computer-aided decision-making based on incomplete data
  • 1991 - EURO Gold Medal
  • Fellow of the International Federation for Information Processing (IFIP) for his work in the areas of dominance-based rough set theory and robust ordinal regression.
  • Fellow of the International Federation for Information Processing (IFIP) for his work in the areas of dominance-based rough set theory and robust ordinal regression.
  • Fellow of the International Federation for Information Processing (IFIP) for his work in the areas of dominance-based rough set theory and robust ordinal regression.
  • Fellow of the International Federation for Information Processing (IFIP) for his work in the areas of dominance-based rough set theory and robust ordinal regression.
  • Fellow of the International Federation for Information Processing (IFIP) for his work in the areas of dominance-based rough set theory and robust ordinal regression.

Overview

Roman Słowiński is affiliated with the Poznań University of Technology in Poland. Their research spans the fields of Computer Science and Decision Sciences, with a notable focus on Multi-Criteria Decision Making and Rough Sets and Fuzzy Logic.

Their work often intersects the following subfields:

  • Management Science and Operations Research
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Information Systems
  • Statistics and Probability

Research topics frequently covered in their publications include:

  • Multi-Criteria Decision Making
  • Rough Sets and Fuzzy Logic
  • Data Mining Algorithms and Applications
  • Bayesian Modeling and Causal Inference
  • Fuzzy Systems and Optimization
  • Advanced Algebra and Logic
  • Cognitive Science and Mapping

Some of the recent papers authored or coauthored by Roman Słowiński are:

  • How to support the application of multiple criteria decision analysis? Let us start with a comprehensive taxonomy, 2020, Omega
  • Auto loan fraud detection using dominance-based rough set approach versus machine learning methods, 2020, Expert Systems with Applications
  • Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda, 2023, European Journal of Operational Research
  • Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction, 2021, Omega
  • Proper and improper uses of MCDA methods in energy systems analysis, 2022, Decision Support Systems

Roman Słowiński's frequent coauthors include:

  • Salvatore Greco
  • Chris Cornelis
  • Marko Palangetić
  • Miłosz Kadziński
  • Marco Cinelli

Their research is published in a variety of venues, with repeated contributions to:

  • European Journal of Operational Research
  • arXiv (Cornell University)
  • Omega
  • Information Sciences
  • Knowledge-Based Systems

Roman Słowiński has received several recognitions and awards over the course of their career, including:

  • Fellow of the Institute for Operations Research and the Management Sciences (INFORMS), 2019
  • IEEE Fellow, 2017, for contributions to dominance-based rough set theory, robust ordinal regression, and preference learning
  • Polish Academy of Science membership, 2013
  • Member of Academia Europaea, 2013
  • Prize of the Foundation for Polish Science (Nagroda Fundacji na rzecz Nauki Polskiej), 2005, for developing a methodology for computer-aided decision-making based on incomplete data
  • EURO Gold Medal, 1991
  • Fellow of the International Federation for Information Processing (IFIP), for work in dominance-based rough set theory and robust ordinal regression

Best Publications

  • Rough sets

    Zdzislaw Pawlak;Jerzy Grzymala-Busse;Roman Slowinski;Wojciech Ziarko

  • Rough sets theory for multicriteria decision analysis

    Salvatore Greco;Benedetto Matarazzo;Roman Slowinski

  • Rough Sets and Current Trends in Computing

    Salvatore Greco;Yutaka Hata;Shoji Hirano;Masahiro Inuiguchi

  • Multiobjective Optimization: Interactive and Evolutionary Approaches

    Jürgen Branke;Kalyanmoy Deb;Kaisa Miettinen;Roman Słowiński

  • A generalized definition of rough approximations based on similarity

    R. Slowinski;D. Vanderpooten

  • Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory

    Roman Slowinski

  • Business failure prediction using rough sets

    A. I. Dimitras;Roman Slowinski;Robert Susmaga;Constantin Zopounidis

  • Rough approximation of a preference relation by dominance relations

    Salvatore Greco;Benedetto Matarazzo;Roman Slowinski

  • Rough approximation by dominance relations

    Salvatore Greco;Benedetto Matarazzo;Roman Slowinski

  • Inferring an ELECTRE TRI Model from Assignment Examples

    V. Mousseau;R. Slowinski

  • Ordinal regression revisited: multiple criteria ranking using a set of additive value functions

    Salvatore Greco;Vincent Mousseau;Roman Słowiński;Roman Słowiński

  • Rough sets methodology for sorting problems in presence of multiple attributes and criteria

    Salvatore Greco;Benedetto Matarazzo;Roman Slowinski

  • An Overview of ELECTRE Methods and their Recent Extensions

    José Rui Figueira;Salvatore Greco;Bernard Roy;Roman Słowiński;Roman Słowiński

  • ROUGH SET REDUCTION OF ATTRIBUTES AND THEIR DOMAINS FOR NEURAL NETWORKS

    Jacek Jelonek;Krzysztof Krawiec;Roman Slowiński

  • A user-oriented implementation of the ELECTRE-TRI method integrating preference elicitation support

    V. Mousseau;R. Slowinski;P. Zielniewicz

  • Application of the Rough Set Approach to Evaluation of Bankruptcy Risk

    R. Slowinski;C. Zopounidis

  • Fuzzy sets in decision analysis, operations research and statistics

    Roman Słowiński

  • Fuzzy Similarity Relation as a Basis for Rough Approximations

    Salvatore Greco;Benedetto Matarazzo;Roman Slowinski

  • Forty years of the European Journal of Operational Research: A bibliometric overview

    Sigifredo Laengle;José M. Merigó;Jaime Miranda;Roman Slowinski

  • A multicriteria fuzzy linear programming method for water supply system development planning

    R Slowinski

  • Rough sets : New horizons in commercial and industrial AI

    Z. Pawlak;J. Grzymala-Busse;R. Slowinski;W. Ziarko

Frequent Co-Authors

Salvatore Greco
Salvatore Greco University of Portsmouth
Benedetto Matarazzo
Benedetto Matarazzo University of Catania
Miłosz Kadziński
Miłosz Kadziński Poznań University of Technology
Jerzy Stefanowski
Jerzy Stefanowski Poznań University of Technology
Masahiro Inuiguchi
Masahiro Inuiguchi Osaka University
Vincent Mousseau
Vincent Mousseau CentraleSupélec
Bernard Roy
Bernard Roy Paris Dauphine University
José Rui Figueira
José Rui Figueira Instituto Superior Técnico
Zdzisław Pawlak
Zdzisław Pawlak Polish Academy of Sciences
Jan Weglarz
Jan Weglarz Poznań University of Technology

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