World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
7344
World Ranking
8834
National Ranking
9

Marko Grobelnik 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 Marko Grobelnik 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: 278 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Marko Grobelnik 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 Marko Grobelnik 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Marko Grobelnik is affiliated with the Jožef Stefan Institute in Slovenia and conducts research primarily in the field of Computer Science, with additional work in Social Sciences. Their research contributions span various subfields, including Artificial Intelligence, Sociology and Political Science, Information Systems, Statistical and Nonlinear Physics, and Epidemiology.

The scientist's recent publications cover multiple aspects of their research focus. Notable papers include:

  • "Meaningful Big Data Integration for a Global COVID-19 Strategy" (2020) published in IEEE Computational Intelligence Magazine
  • "From fear to action: AI governance and opportunities for all" (2023) published in Frontiers in Computer Science
  • "Seeking information about assistive technology: Exploring current practices, challenges, and the need for smarter systems" (2023) published in International Journal of Human-Computer Studies
  • "Why is a document relevant? Understanding the relevance scores in cross-lingual document retrieval" (2022) published in Knowledge-Based Systems
  • "Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination" (2022) published in IEEE Access

Marko Grobelnik has collaborated frequently with several colleagues. Among the most frequent coauthors are:

  • Dunja Mladenić
  • Abdul Sittar
  • M. Besher Massri
  • João Pita Costa
  • Luka Stopar

The scientist's work appears in a range of publication venues. Some of the most common outlets include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Access
  • Knowledge-Based Systems
  • Journal of Intelligent Information Systems

Their main fields of study involve advanced computational methods and interdisciplinary applications. The subfields of study highlight a blend of technological and social science domains, with emphasis on:

  • Artificial Intelligence
  • Sociology and Political Science
  • Information Systems
  • Statistical and Nonlinear Physics
  • Epidemiology

The scientist's research topics concentrate on computational and analytical techniques, including:

  • Advanced Text Analysis Techniques
  • Topic Modeling
  • Misinformation and Its Impacts
  • Sentiment Analysis and Opinion Mining
  • Data-Driven Disease Surveillance
  • Natural Language Processing Techniques
  • Computational and Text Analysis Methods

Best Publications

  • A SURVEY OF ONTOLOGY EVALUATION TECHNIQUES

    Janez Brank;Marko Grobelnik

  • Feature Selection for Unbalanced Class Distribution and Naive Bayes

    Dunja Mladenic;Marko Grobelnik

  • Deep Belief Networks

    Unknown

  • Learning nonrecursive definitions of relations with LINUS

    Nada Lavrač;Sašo Džeroski;Marko Grobelnik

  • Feature selection using linear classifier weights: interaction with classification models

    Dunja Mladenić;Janez Brank;Marko Grobelnik;Natasa Milic-Frayling

  • Semi-automatic construction of topic ontologies

    Blaz Fortuna;Dunja Mladenic;Marko Grobelnik

  • Visualization of Text Document Corpus

    Blaz Fortuna;Marko Grobelnik;Dunja Mladenic

  • Feature selection on hierarchy of web documents

    Dunja Mladenić;Marko Grobelnik

  • OntoGen: semi-automatic ontology editor

    Blaz Fortuna;Marko Grobelnik;Dunja Mladenic

  • Data sparsity issues in the collaborative filtering framework

    Miha Grčar;Dunja Mladenič;Blaž Fortuna;Marko Grobelnik

  • Event registry: learning about world events from news

    Gregor Leban;Blaz Fortuna;Janez Brank;Marko Grobelnik

  • Interaction of Feature Selection Methods and Linear Classification Models

    Janez Brank;Marko Grobelnik;Nataša Milic-Frayling

  • The Semanic Web: Research and Applications

    Grigoris Antoniou;Marko Grobelnik;Elena Simperl;Bijan Parsia

  • Learning Sub-structures of Document Semantic Graphs for Document Summarization

    Jurij Leskovec;Marko Grobelnik;Natasa Milic-Frayling

  • A Capillary Computing Architecture for Dynamic Internet of Things: Orchestration of Microservices from Edge Devices to Fog and Cloud Providers.

    Salman Taherizadeh;Vlado Stankovski;Vlado Stankovski;Marko Grobelnik

  • Subspace, Latent Structure and Feature Selection

    Craig Saunders;Marko Grobelnik;Steve Gunn;John Shawe-Taylor

  • Proceedings of the 3rd international workshop on Link discovery

    Jafar Adibi;Marko Grobelnik;Dunja Mladenic;Patrick Pantel

  • Feature Selection Using Linear Support Vector Machines

    Janez Brank;Marko Grobelnik

  • Fuzzy Systems

    Unknown

  • Feature Selection Using Support Vector Machines

    J Brank;M Grobelnik;N Milic-Frayling;D Mladenic

  • Monitoring Network Evolution using MDL

    J. Ferlez;C. Faloutsos;J. Leskovec;D. Mladenic

  • SEMI-AUTOMATIC DATA-DRIVEN ONTOLOGY CONSTRUCTION SYSTEM

    Marko Grobelnik

Frequent Co-Authors

Dunja Mladenic
Dunja Mladenic Jožef Stefan Institute
John Shawe-Taylor
John Shawe-Taylor University College London
Elena Simperl
Elena Simperl King's College London
Andreas Hotho
Andreas Hotho University of Würzburg
Grigoris Antoniou
Grigoris Antoniou University of Huddersfield
Bijan Parsia
Bijan Parsia University of Manchester
Wray Buntine
Wray Buntine VinUniversity
Dimitris Plexousakis
Dimitris Plexousakis University of Crete
Steve R. Gunn
Steve R. Gunn University of Southampton

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