World's Best Scientists 2026 revealed!
Stan Szpakowicz

Stan Szpakowicz

D-Index & Metrics

Computer Science

D-Index
31
Citations
7052
World Ranking
13386
National Ranking
518

Stan Szpakowicz 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 Stan Szpakowicz 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: 148 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Stan Szpakowicz 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 Stan Szpakowicz 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: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Stan Szpakowicz is affiliated with the University of Ottawa in Canada and has contributed to the field of computer science, focusing primarily on artificial intelligence. Their research spans several specialized areas including natural language processing techniques, topic modeling, advanced graph neural networks, speech and dialogue systems, semantic web and ontologies, as well as business process modeling and analysis.

The scientist's publication record includes papers in venues such as Synthesis Lectures on Human Language Technologies and arXiv (Cornell University). Notable recent works include:

  • Semantic Relations Between Nominals, Second Edition (2021), published in Synthesis Lectures on Human Language Technologies
  • Semantic Relations and Deep Learning (2020), published in arXiv (Cornell University)

Stan Szpakowicz has co-authored multiple papers with several frequent collaborators. These include Vivi Năstase, with whom they have collaborated on nine publications; Preslav Nakov, with eight shared works; and Diarmuid Ó Séagdha, also with eight joint publications.

Their book publications include at least one title published by Morgan & Claypool Publishers: "Semantic Relations Between Nominals, Second Edition" released in 2021.

Szpakowicz's work integrates various main topics such as natural language processing techniques and topic modeling, areas that feature prominently in their eight publications within artificial intelligence. The inclusion of advanced graph neural networks points to an interest in machine learning approaches, while research into speech and dialogue systems aligns with human-computer interaction subfields.

Frequent publication venues for Szpakowicz's research reflect a focus on human language technologies and preprint dissemination, offering contributions to both established and emergent research outlets.

Best Publications

  • Beyond accuracy, f-score and ROC: a family of discriminant measures for performance evaluation

    Marina Sokolova;Nathalie Japkowicz;Stan Szpakowicz

  • SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • Identifying expressions of emotion in text

    Saima Aman;Stan Szpakowicz

  • SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • Roget’s thesaurus and semantic similarity

    Mario Jarmasz;Stan Szpakowicz

  • SemEval-2007 Task 04: Classification of Semantic Relations between Nominals

    Roxana Girju;Preslav Nakov;Vivi Nastase;Stan Szpakowicz

  • Detecting Emotion Stimuli in Emotion-Bearing Sentences

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • A WordNet-based algorithm for word sense disambiguation

    Xiaobin Li;Stan Szpakowicz;Stan Matwin

  • Negoplan: an expert system shell for negotiation support

    S. Matwin;S. Szpakowicz;Z. Koperczak;G.E. Kersten

  • Semi-Automatic Recognition of Noun Modifier Relationships

    Ken Barker;Stan Szpakowicz

  • Restructurable representations of negotiation

    Gregory E. Kersten;Wojtek Michalowski;Stan Szpakowicz;Zbig Koperczak

  • Using Roget's Thesaurus for Fine-grained Emotion Recognition.

    Saima Aman;Stan Szpakowicz

  • Hierarchical versus Flat Classification of Emotions in Text

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz

  • Learning noun-modifier semantic relations with corpus-based and WordNet-based features

    Vivi Nastase;Jelber Sayyad-Shirabad;Marina Sokolova;Stan Szpakowicz

  • Classification of semantic relations between nominals

    Roxana Girju;Preslav Nakov;Preslav Nakov;Vivi Nastase;Stan Szpakowicz;Stan Szpakowicz

  • SemEval-2 Task 9: The Interpretation of Noun Compounds Using Paraphrasing Verbs and Prepositions

    Cristina Butnariu;Su Nam Kim;Preslav Nakov;Diarmuid Ó Séaghdha

  • Summarizing short stories

    Anna Kazantseva;Stan Szpakowicz

  • plWordNet 3.0 - a Comprehensive Lexical-Semantic Resource.

    Marek Maziarz;Maciej Piasecki;Ewa Rudnicka;Stan Szpakowicz

  • SemEval-2010 Task 9: The Interpretation of Noun Compounds Using Paraphrasing Verbs and Prepositions

    Cristina Butnariu;Su Nam Kim;Preslav Nakov;Diarmuid Ó Séaghdha

  • Prior and contextual emotion of words in sentential context

    Diman Ghazi;Diana Inkpen;Stan Szpakowicz;Stan Szpakowicz

  • A survey of book recommender systems

    Haifa Alharthi;Diana Inkpen;Stan Szpakowicz

  • Semantic Relations Between Nominals

    Vivi Nastase;Preslav Nakov;Diarmuid Saghdha;Stan Szpakowicz

  • Multi-way classification of semantic relations between pairs of nominals

    Iris Hendrickx;Su Nam Kim;Zornitsa Kozareva;Preslav Nakov

  • SemEval-2013 Task 4: Free Paraphrases of Noun Compounds

    Iris Hendrickx;Preslav Nakov;Stan Szpakowicz;Zornitsa Kozareva

Frequent Co-Authors

Preslav Nakov
Preslav Nakov Mohamed bin Zayed University of Artificial Intelligence
Gregory E. Kersten
Gregory E. Kersten Concordia University
Diana Inkpen
Diana Inkpen University of Ottawa
Stan Matwin
Stan Matwin Dalhousie University
Sebastian Padó
Sebastian Padó University of Stuttgart
Peter D. Turney
Peter D. Turney Ronin Institute
Nathalie Japkowicz
Nathalie Japkowicz American University
Saif M. Mohammad
Saif M. Mohammad National Research Council Canada
Rada Mihalcea
Rada Mihalcea University of Michigan–Ann Arbor
Christiane Fellbaum
Christiane Fellbaum Princeton University

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