World's Best Scientists 2026 revealed!
Natasa Milic-Frayling

Natasa Milic-Frayling

D-Index & Metrics

Computer Science

D-Index
39
Citations
6676
World Ranking
9742
National Ranking
608

Natasa Milic-Frayling 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 Natasa Milic-Frayling 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: 139 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

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

Natasa Milic-Frayling 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 Natasa Milic-Frayling 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Natasa Milic-Frayling is affiliated with Intact Digital in the United Kingdom. Their primary field of study is Computer Science with a specific focus on Artificial Intelligence, accounting for most of their work. Additional subfields include Human-Computer Interaction, Computer Science Applications, Electrical and Electronic Engineering, and Computer Vision and Pattern Recognition.

The research topics covered by Natasa Milic-Frayling include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Speech and dialogue systems
  • Innovative Human-Technology Interaction
  • Open Source Software Innovations
  • Green IT and Sustainability
  • Text Readability and Simplification

The scientist has contributed to several publication venues, with a strong presence in:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • TUGraz OPEN Library (Graz University of Technology)

Key recent papers authored or co-authored by Natasa Milic-Frayling include:

  • "LAraBench: Benchmarking Arabic AI with Large Language Models," 2023, published in arXiv (Cornell University)
  • "On the Cusp: Computing Thrills and Perils and Professional Awakening," 2023, published in Proceedings of the VLDB Endowment
  • "Contextual Knowledge Learning For Dialogue Generation," 2023, published in arXiv (Cornell University)
  • "Feature Selection for the Classification of Large Document Collections," 2020, published in TUGraz OPEN Library (Graz University of Technology)
  • "Instantiation-based Formalization of Logical Reasoning Tasks using Language Models and Logical Solvers," 2025, published in arXiv (Cornell University)

Frequent co-authors in Natasa Milic-Frayling's work include:

  • Shammur Absar Chowdhury
  • Basel Mousi
  • Fahim Dalvi
  • Nadir Durrani
  • Firoj Alam

Best Publications

  • Analyzing (social media) networks with NodeXL

    Marc A. Smith;Ben Shneiderman;Natasa Milic-Frayling;Eduarda Mendes Rodrigues

  • Hyperlink preview utility and method

    Ralph Sommerer;Robert Tucker;Natasa Milic-Frayling

  • Navigating a resource browser session

    Ralph Sommerer;Robert Tucker;Natasa Milic-Frayling;Jurij Leskovec

  • Intelligent backward resource navigation

    Natasa Milic-Frayling;Samuel Gavin Smyth;Kerry Rodden;Ralph Sommerer

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

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

  • Resource browser sessions search

    Ralph Sommerer;Robert Tucker;Natasa Milic-Frayling;Jurij Leskovec

  • Worker types and personality traits in crowdsourcing relevance labels

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

  • Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

    Mika Rautiainen;Timo Korhonen;Edward Mutafungwa;Eila Ovaska

  • Crowdsourcing for book search evaluation: impact of hit design on comparative system ranking

    Gabriella Kazai;Jaap Kamps;Marijn Koolen;Natasa Milic-Frayling

  • Facility for highlighting documents accessed through search or browsing

    Natasa Milic-Frayling;Ralph Sommerer

  • User interface for a resource search tool

    Natasa Milic-Frayling;Ralph Sommerer

  • An analysis of human factors and label accuracy in crowdsourcing relevance judgments

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

  • Interaction of Feature Selection Methods and Linear Classification Models

    Janez Brank;Marko Grobelnik;Nataša Milic-Frayling

  • Personalized information communications

    Natasa Milic-Frayling;Jamie Costello;Anthony Francis Frayling

  • The face of quality in crowdsourcing relevance labels: demographics, personality and labeling accuracy

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

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

    Jurij Leskovec;Marko Grobelnik;Natasa Milic-Frayling

  • Materializing the query with facet-streams: a hybrid surface for collaborative search on tabletops

    Hans-Christian Jetter;Jens Gerken;Michael Zöllner;Harald Reiterer

  • Smartback: supporting users in back navigation

    Natasa Milic-Frayling;Rachel Jones;Kerry Rodden;Gavin Smyth

  • On ranking the effectiveness of searches

    Vishwa Vinay;Ingemar J. Cox;Natasa Milic-Frayling;Ken Wood

  • Do You Know the Way to SNA?: A Process Model for Analyzing and Visualizing Social Media Network Data

    D. L. Hansen;D. Rotman;E. Bonsignore;N. Milic-Frayling

Frequent Co-Authors

Gabriella Kazai
Gabriella Kazai Microsoft (United States)
Ingemar J. Cox
Ingemar J. Cox University College London
Marko Grobelnik
Marko Grobelnik Jožef Stefan Institute
Alan F. Blackwell
Alan F. Blackwell University of Cambridge
Dunja Mladenic
Dunja Mladenic Jožef Stefan Institute
Carlos Soares
Carlos Soares University of Porto
Marc A. Smith
Marc A. Smith Connected Action Consulting Group
Jaap Kamps
Jaap Kamps University of Amsterdam
Jukka Riekki
Jukka Riekki University of Oulu
ChengXiang Zhai
ChengXiang Zhai University of Illinois at Urbana-Champaign

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