World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
5089
World Ranking
10860
National Ranking
4520

Gabriella Kazai 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 Gabriella Kazai 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: 162 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

Gabriella Kazai 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 Gabriella Kazai 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Gabriella Kazai is affiliated with Microsoft in the United States. Their work primarily spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Computer Science Applications, Information Systems, Sociology and Political Science, and Information Systems and Management.

Their research covers a range of topics, notably Mobile Crowdsensing and Crowdsourcing, Topic Modeling, Misinformation and Its Impacts, Information Retrieval and Search Behavior, Advanced Text Analysis Techniques, Spam and Phishing Detection, and Hate Speech and Cyberbullying Detection.

Kazai has contributed to peer-reviewed publications in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the ACM on Human-Computer Interaction
  • First Monday

Selected recent papers authored or coauthored by Kazai include:

  • When Are Search Completion Suggestions Problematic?, 2020, Proceedings of the ACM on Human-Computer Interaction
  • On the social and technical challenges of Web search autosuggestion moderation, 2022, First Monday
  • Rethinking Semi-supervised Learning with Language Models, 2023, arXiv (Cornell University)
  • Proceedings of the CSCW 2021 Workshop -- Investigating and Mitigating Biases in Crowdsourced Data, 2021, arXiv (Cornell University)

Gabriella Kazai has collaborated frequently with several researchers, including:

  • Emine Yılmaz
  • Alexandra Olteanu
  • Fernando Díaz
  • Bhaskar Mitra
  • Anlei Dong

Best Publications

  • Initiative for the Evaluation of XML Retrieval

    Gabriella Kazai

  • Community-based bayesian aggregation models for crowdsourcing

    Matteo Venanzi;John Guiver;Gabriella Kazai;Pushmeet Kohli

  • In search of quality in crowdsourcing for search engine evaluation

    Gabriella Kazai

  • Worker types and personality traits in crowdsourcing relevance labels

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

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

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

  • Advances in XML Information Retrieval and Evaluation

    Norbert Fuhr;Mounia Lalmas;Saadia Malik;Gabriella Kazai

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

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

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

    Gabriella Kazai;Jaap Kamps;Natasa Milic-Frayling

  • The overlap problem in content-oriented XML retrieval evaluation

    Gabriella Kazai;Mounia Lalmas;Arjen P. de Vries

  • Overview of the Initiative for the Evaluation of XML retrieval (INEX) 2002.

    Norbert Gövert;Gabriella Kazai

  • INEX 2005 evaluation measures

    Gabriella Kazai;Mounia Lalmas

  • INEX 2007 Evaluation Measures

    Jaap Kamps;Jovan Pehcevski;Gabriella Kazai;Mounia Lalmas

  • INEX 2005 evaluation measures

    Gabriella Kazai;Mounia Lalmas

  • Advances in Information Retrieval Theory

    Leif Azzopardi;Gabriella Kazai;Stephen Robertson;Stefan Rüger

  • Overview of INEX 2005

    Saadia Malik;Gabriella Kazai;Mounia Lalmas;Norbert Fuhr

  • Towards a science of user engagement.

    Simon Attfield;Gabriella Kazai;Mounia Lalmas;Benjamin Piwowarski

  • Overview of the INEX 2011 Books and Social Search Track

    Marijn Koolen;Gabriella Kazai;Jaap Kamps;Antoine Doucet

  • On aggregating labels from multiple crowd workers to infer relevance of documents

    Mehdi Hosseini;Ingemar J. Cox;Nataša Milić-Frayling;Gabriella Kazai

  • Overview of the INEX 2013 Social Book Search Track

    Marijn Koolen;Gabriella Kazai;Michael Preminger;Antoine Doucet

  • Towards methods for the collective gathering and quality control of relevance assessments

    Gabriella Kazai;Natasa Milic-Frayling;Jamie Costello

Frequent Co-Authors

Jaap Kamps
Jaap Kamps University of Amsterdam
Norbert Fuhr
Norbert Fuhr University of Duisburg-Essen
Ralf Schenkel
Ralf Schenkel University of Trier
Stephen Robertson
Stephen Robertson University College London
Peter Brusilovsky
Peter Brusilovsky University of Pittsburgh
Dawei Song
Dawei Song The Open University
Leif Azzopardi
Leif Azzopardi University of Strathclyde
Nick Craswell
Nick Craswell Microsoft (United States)

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