World's Best Scientists 2026 revealed!
Silvia Miksch

Silvia Miksch

D-Index & Metrics

Computer Science

D-Index
54
Citations
11439
World Ranking
4574
National Ranking
30

Silvia Miksch 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 Silvia Miksch 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: 294 publications — 73rd percentile

73% of scientists in this discipline score the same or lower.

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

Silvia Miksch 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 Silvia Miksch 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: 54 D-Index — 69th percentile

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

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

Overview

Silvia Miksch is a researcher affiliated with TU Wien in Austria, specializing primarily in computer science with a focus on data visualization and analytics. Their work spans multiple subfields including computer vision and pattern recognition, signal processing, artificial intelligence, statistical and nonlinear physics, and ecological modeling.

The main topics of their research include:

  • Data Visualization and Analytics
  • Video Analysis and Summarization
  • Complex Network Analysis Techniques
  • Data Management and Algorithms
  • Species Distribution and Climate Change
  • Semantic Web and Ontologies
  • Blind Source Separation Techniques

Silvia Miksch's recent papers reflect their engagement in advancing visual analytics and network visualization. Notable publications include:

  • "A theoretical model for pattern discovery in visual analytics," 2020, Visual Informatics
  • "Perspectives of visualization onboarding and guidance in VA," 2022, Visual Informatics
  • "Are We There Yet? A Roadmap of Network Visualization from Surveys to Task Taxonomies," 2023, Computer Graphics Forum
  • "Guide Me in Analysis: A Framework for Guidance Designers," 2020, Computer Graphics Forum
  • "A Typology of Guidance Tasks in Mixed-Initiative Visual Analytics Environments," 2022, Computer Graphics Forum

Frequent co-authors collaborating with Silvia Miksch include:

  • Christian Tominski
  • Davide Ceneda
  • Alessio Arleo
  • Wolfgang Aigner
  • Markus Bögl

Their research output has appeared in several key publication venues, demonstrating active contributions to the field of visualization and computer graphics. These venues are:

  • IEEE Transactions on Visualization and Computer Graphics
  • Computer Graphics Forum
  • arXiv (Cornell University)
  • Visual Informatics
  • IEEE Computer Graphics and Applications

In addition to articles, Silvia Miksch has authored a book published by Springer Nature titled "Visualization of Time-Oriented Data" in 2023.

Best Publications

  • Visualization of Time-Oriented Data

    Wolfgang Aigner;Silvia Miksch;Heidrun Schumann;Christian Tominski

  • Comparing computer-interpretable guideline models: a case-study approach.

    Mor Peleg;Samson W. Tu;Jonathan Bury;Paolo Ciccarese

  • THE ASGAARD PROJECT: A TASK-SPECIFIC FRAMEWORK FOR THE APPLICATION AND CRITIQUING OF TIME-ORIENTED CLINICAL GUIDELINES

    Yuval Shahar;Silvia Miksch;Peter D. Johnson

  • Visualizing time-oriented data-A systematic view

    Wolfgang Aigner;Silvia Miksch;Wolfgang Müller;Heidrun Schumann

  • Visual Methods for Analyzing Time-Oriented Data

    W. Aigner;S. Miksch;W. Muller;H. Schumann

  • Interactive Information Visualization to Explore and Query Electronic Health Records

    Alexander Rind;Taowei David Wang;Wolfgang Aigner;Silvia Miksch

  • Characterizing Guidance in Visual Analytics

    Davide Ceneda;Theresia Gschwandtner;Thorsten May;Silvia Miksch

  • Visualization of Cultural Heritage Collection Data: State of the Art and Future Challenges

    Florian Windhager;Paolo Federico;Gunther Schreder;Katrin Glinka

  • Connecting time-oriented data and information to a coherent interactive visualization

    Ragnar Bade;Stefan Schlechtweg;Silvia Miksch

  • ASBRU: A TASK-SPECIFIC, INTENTION-BASED, AND TIME-ORIENTED LANGUAGE FOR REPRESENTING SKELETAL PLANS

    Silvia Miksch;Yuval Shahar;Peter Johnson

  • Semantic depth of field

    R. Kosara;S. Miksch;H. Hauser

  • Special Section on Visual Analytics: A matter of time: Applying a data-users-tasks design triangle to visual analytics of time-oriented data

    Silvia Miksch;Wolfgang Aigner

  • Focus+context taken literally

    R. Kosara;S. Miksch;H. Hauser

  • Utilizing temporal data abstraction for data validation and therapy planning for artificially ventilated newborn infants

    Silvia Miksch;Werner Horn;Werner Horn;Christian Popow;Franz Paky

  • Improving medical protocols by formal methods

    Annette ten Teije;Mar Marcos;Michel Balser;Joyce van Croonenborg

  • Visualizing Sets and Set-typed Data: State-of-the-Art and Future Challenges

    Bilal Alsallakh;Luana Micallef;Wolfgang Aigner;Helwig Hauser

  • PlanningLines: novel glyphs for representing temporal uncertainties and their evaluation

    W. Aigner;S. Miksch;B. Thurnher;S. Biffl

  • The State-of-the-Art of Set Visualization

    Bilal Alsallakh;Luana Micallef;Luana Micallef;Wolfgang Aigner;Wolfgang Aigner;Helwig Hauser

  • Metaphors of movement: a visualization and user interface for time-oriented, skeletal plans

    Robert Kosara;Silvia Miksch

  • pdf2table: A Method to Extract Table Information from PDF Files.

    Burcu Yildiz;Katharina Kaiser;Silvia Miksch

Frequent Co-Authors

Mor Peleg
Mor Peleg University of Haifa
Yuval Shahar
Yuval Shahar Ben-Gurion University of the Negev
Heidrun Schumann
Heidrun Schumann University of Rostock
Helwig Hauser
Helwig Hauser University of Bergen
Manfred Reichert
Manfred Reichert University of Ulm
Gennady Andrienko
Gennady Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems
Natalia Andrienko
Natalia Andrienko Fraunhofer Institute for Intelligent Analysis and Information Systems
Peter J. F. Lucas
Peter J. F. Lucas University of Twente
Christian F. Poets
Christian F. Poets University of Tübingen

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