World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
8267
World Ranking
5769
National Ranking
8

János Abonyi publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where János Abonyi sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 327 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

János Abonyi D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where János Abonyi sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 44 D-Index — 42nd percentile

42% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

János Abonyi is affiliated with the University of Pannonia in Hungary and has contributed extensively to the fields of engineering and computer science. Their research primarily spans industrial and manufacturing engineering, with significant work also in control and systems engineering, artificial intelligence, information systems, and statistical and nonlinear physics.

Their main topics of investigation include digital transformation in industry, flexible and reconfigurable manufacturing systems, manufacturing process and optimization, fault detection and control systems, complex network analysis techniques, multi-criteria decision making, and human-automation interaction and safety.

Abonyi's recent published papers cover a range of topics connected to manufacturing systems, sustainability, and digital technologies. Notable papers include:

  • "Focal points for sustainable development strategies-Text mining-based comparative analysis of voluntary national reviews" (2020, Journal of Environmental Management)
  • "Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools" (2020, Computers in Industry)
  • "Current development on the Operator 4.0 and transition towards the Operator 5.0: A systematic literature review in light of Industry 5.0" (2023, Journal of Manufacturing Systems)
  • "Modelling for Digital Twins-Potential Role of Surrogate Models" (2021, Processes)
  • "Real-Time Locating System in Production Management" (2020, Sensors)

Their frequent coauthors include:

  • Tamás Ruppert
  • Tímea Czvetkó
  • Viktor Sebestyén
  • László Nagy
  • Alex Kummer

Abonyi's work is often published in several academic venues, including:

  • IEEE Access
  • Sensors
  • Complexity
  • Heliyon
  • PLoS ONE

They have authored books published by Springer International Publishing and Springer Nature, with titles such as Are Regions Prepared for Industry 4.0? (2020) and Ontology-Based Development of Industry 4.0 and 5.0 Solutions for Smart Manufacturing and Production (2024), as well as Network-Based Analysis of Dynamical Systems (2020).

Best Publications

  • Cluster Analysis for Data Mining and System Identification

    Janos Abonyi;Balazs Feil

  • Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models

    J. Abonyi;R. Babuska;F. Szeifert

  • Supervised fuzzy clustering for the identification of fuzzy classifiers

    Janos Abonyi;Ferenc Szeifert

  • Learning fuzzy classification rules from labeled data

    Johannes A. Roubos;Magne Setnes;Janos Abonyi

  • Fuzzy Model Identification

    János Abonyi

  • Enabling Technologies for Operator 4.0: A Survey

    Tamás Ruppert;Szilárd Jaskó;Tibor Holczinger;János Abonyi

  • Fuzzy Model Identification for Control

    Janos Abonyi

  • Genetic programming for the identification of nonlinear input-output models

    János Madár;János Abonyi;Ferenc Szeifert

  • Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization

    Janos Abonyi;Johannes A. Roubos;Ferenc Szeifert

  • Modified Gath--Geva clustering for fuzzy segmentation of multivariate time-series

    Janos Abonyi;Balazs Feil;Sandor Nemeth;Peter Arva

  • Effective optimization for fuzzy model predictive control

    S. Mollov;R. Babuska;J. Abonyi;H.B. Verbruggen

  • Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools

    Szilárd Jaskó;Adrienn Skrop;Tibor Holczinger;Tibor Chován

  • Correlation based dynamic time warping of multivariate time series

    ZoltáN Bankó;JáNos Abonyi

  • Modelling for Digital Twins—Potential Role of Surrogate Models

    Ágnes Bárkányi;Tibor Chován;Sándor Németh;János Abonyi

  • Identification and Control of Nonlinear Systems Using Fuzzy Hammerstein Models

    J. Abonyi;R. Babuška;M. Ayala Botto;F. Szeifert

  • Learning Fuzzy Classification Rules from Data

    Hans Roubos;Magne Setnes;Janos Abonyi

  • Model Order Selection of Nonlinear Input-Output Models - A Clustering Based Approach

    Balazs Feil;Janos Abonyi;Ferenc Szeifert

  • Computational Intelligence in Data Mining

    Janos Abonyi;Balazs Feil;Ajith Abraham

  • Fuzzy modeling with multivariate membership functions: gray-box identification and control design

    J. Abonyi;R. Babuska;F. Szeifert

  • Real-Time Locating System in Production Management.

    András Rácz-Szabó;Tamás Ruppert;László Bántay;Andreas Löcklin

  • Inverse fuzzy-process-model based direct adaptive control

    János Abonyi;Hans Andersen;Lajos Nagy;Ferenc Szeifert

  • Local and global identification and interpretation of parameters in Takagi-Sugeno fuzzy models

    J. Abonyi;R. Babuska

  • Optimization of Multiple Traveling Salesmen Problem by a Novel Representation Based Genetic Algorithm

    András Király;János Abonyi

Frequent Co-Authors

Robert Babuska
Robert Babuska Delft University of Technology
Ahmet Palazoglu
Ahmet Palazoglu University of California, Davis
Ajith Abraham
Ajith Abraham Sai University
András Guttman
András Guttman University of Debrecen
Francisca Puertas
Francisca Puertas Spanish National Research Council
Sigurd Skogestad
Sigurd Skogestad Norwegian University of Science and Technology

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