World's Best Scientists 2026 revealed!
Ryszard S. Michalski

Ryszard S. Michalski

D-Index & Metrics

Computer Science

D-Index
61
Citations
22398
World Ranking
3002
National Ranking
1471

Ryszard S. Michalski 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 Ryszard S. Michalski 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: 312 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Ryszard S. Michalski 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 Ryszard S. Michalski 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: 61 D-Index — 79th percentile

79% 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

  • 1992 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI)

Overview

Ryszard S. Michalski was affiliated with George Mason University in the United States. Their research contributed to multiple fields including Energy, Engineering, and Social Sciences, with notable work in the subfields of Renewable Energy, Sustainability and the Environment, Biomedical Engineering, Political Science and International Relations, Materials Chemistry, and History.

Their recent publications covered diverse topics combining scientific and cultural perspectives. Noteworthy papers include:

  • A Comparative Analysis of Emissions from a Compression-Ignition Engine Powered by Diesel, Rapeseed Biodiesel, and Biodiesel from Chlorella protothecoides Biomass Cultured under Different Conditions (2021, Atmosphere)
  • Udział polskiego duchowieństwa katolickiego na Pomorzu w procesie narodowotwórczym XIX-XXI w. (2022, Fides Ratio et Patria Studia Toruńskie)
  • The Emissions of a Compression-Ignition Engine Fuelled by a Mixture of Crude Oil and Biodiesel from the Lipids Accumulated in the Waste Glycerol-Fed Culture of Schizochytrium sp. (2024, Energies)

These works demonstrated a focus on biofuel production, engine emissions, and Polish historical and cultural studies, indicating an interdisciplinary approach to research topics.

Frequent co-authors that collaborated with Michalski included Marcin Dębowski, Marcin Zieliński, and Joanna Kazimierowicz. The consistent cooperation with these colleagues suggests significant collaborative efforts in their research area.

Their main research topics encompassed:

  • Algal biology and biofuel production
  • Biodiesel Production and Applications
  • Catalytic Processes in Materials Science
  • Polish Historical and Cultural Studies
  • Historical and Cultural Studies of Poland
  • European Politics and Security
  • Microbial Metabolic Engineering and Bioproduction

Michalski published in several academic venues including Atmosphere, Fides Ratio et Patria Studia Toruńskie, and Energies, reflecting a combination of environmental sciences and social sciences literature presence.

In recognition of contributions to the scientific community, they were awarded the title Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 1992.

Best Publications

  • A theory and methodology of inductive learning

    Ryszard S. Michalski

  • Machine Learning: An Artificial Intelligence Approach

    R. S. Michalski;J. G. Carbonell;T. M. Mitchell

  • The multi-purpose incremental learning system AQ15 and its testing application to three medical domains

    Ryszard S. Michalski;Igor Mozetic;Jiarong Hong;Nada Lavrac

  • Learning from Observation: Conceptual Clustering

    Ryszard S. Michalski;Robert E. Stepp

  • The MONK's problems: A Performance Comparison of Different Learning Algorithms

    Sebastian B. Thrun;Jerzy W. Bala;Eric Bloedorn;Ivan Bratko

  • Machine Learning and Data Mining; Methods and Applications

    Ryszard S. Michalski;Ivan Bratko;Avan Bratko

  • Pattern Recognition as Rule-Guided Inductive Inference

    Ryszard S. Michalski

  • An Overview of Machine Learning

    Jaime G. Carbonell;Ryszard S. Michalski;Tom M. Mitchell

  • The logic of plausible reasoning: A core theory.

    Allan M. Collins;Ryszard S. Michalski

  • Automated Construction of Classifications: Conceptual Clustering Versus Numerical Taxonomy

    Ryszard S. Michalski;Robert E. Stepp

  • On the Quasi-Minimal Solution of the General Covering Problem

    Ryszard S. Michalski

  • Understanding the Nature of Learning: Issues and Research Directions

    Ryszard S. Michalski

  • Machine learning: an artificial intelligence approach volume III

    Yves Kodratoff;Ryszard S. Michalski

  • A Comparative Review of Selected Methods for Learning from Examples

    Thomas G. Dietterich;Ryszard S. Michalski

  • Categories and Concepts: Theoretical Views and Inductive Data Analysis

    I. Van Mechelen;J. Hampton;R. Michalski;P. Theuns

  • LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning

    Ryszard S. Michalski

  • Conceptual Clustering: Inventing Goal-Oriented Classifications of Structured Objects

    Robert E. Stepp;Ryszard S. Michalski

  • Hypothesis-Driven Constructive Induction in AQ17-HCI: A Method and Experiments

    Janusz Wnek;Ryszard S. Michalski

  • Integrating quantitative and qualitative discovery in the ABACUS system

    Brian C. Falkenhainer;Ryszard S. Michalski

  • Inductive learning of structural descriptions: Evaluation criteria and comparative review of selected methods

    Thomas G. Dietterich;Ryszard S. Michalski

Frequent Co-Authors

Tom M. Mitchell
Tom M. Mitchell Carnegie Mellon University
Jaime G. Carbonell
Jaime G. Carbonell Carnegie Mellon University
Stan Matwin
Stan Matwin Dalhousie University
Thomas G. Dietterich
Thomas G. Dietterich Oregon State University
Azriel Rosenfeld
Azriel Rosenfeld University of Maryland, College Park
Allan Collins
Allan Collins Northwestern University
Yiannis Aloimonos
Yiannis Aloimonos University of Maryland, College Park
Ivan Bratko
Ivan Bratko University of Ljubljana
Kenneth de Jong
Kenneth de Jong George Mason University
Herbert A. Simon
Herbert A. Simon Carnegie Mellon University

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