World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
12620
World Ranking
12357
National Ranking
431

Andrea Esuli 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 Andrea Esuli 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: 149 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.

Andrea Esuli 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 Andrea Esuli 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: 33 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Andrea Esuli is affiliated with the Institute of Information Science and Technologies in Italy and has published extensively in the field of Computer Science, with a particular focus on Artificial Intelligence. Their research spans various subfields and topics related to machine learning, information retrieval, and multimodal data analysis.

Esuli's notable research contributions include the following papers:

  • Fine-grained visual textual alignment for cross-modal retrieval using transformer encoders (2021), published in CINECA IRIS Institutial research information system (University of Pisa)
  • MARC: a robust method for multiple-aspect trajectory classification via space, time, and semantic embeddings (2020), published in International Journal of Geographical Information Systems
  • Transformer reasoning network for image-text matching and retrieval (2020), published in Zenodo (CERN European Organization for Nuclear Research)
  • Cross-Lingual Sentiment Quantification (2020), published in IEEE Intelligent Systems
  • Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach (2023), published in ArTS Archivio della ricerca di Trieste (University of Trieste)

Their main research topics are diverse and include:

  • Text and Document Classification Technologies
  • Topic Modeling
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Imbalanced Data Classification Techniques

Frequent co-authors who have collaborated with Andrea Esuli include:

  • Fabrizio Sebastiani
  • Alejandro Moreo
  • Alessandro Fabris
  • Fabrizio Falchi
  • Nicola Messina

Andrea Esuli's publications are often found in prominent venues such as:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • ACM Transactions on Information Systems
  • Data Mining and Knowledge Discovery
  • CINECA IRIS Institutial research information system (University of Pisa)

In addition to numerous research papers, they have authored a book titled Learning to Quantify (2023) published in the "Information Retrieval Series."

Best Publications

  • SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining.

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

  • SENTIWORDNET: A Publicly Available Lexical Resource for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Determining the semantic orientation of terms through gloss classification

    Andrea Esuli;Fabrizio Sebastiani

  • Determining Term Subjectivity and Term Orientation for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Evaluation Measures for Ordinal Regression

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

  • SentiWordNet: A High-Coverage Lexical Resource for Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • PageRanking WordNet Synsets: An Application to Opinion Mining

    Andrea Esuli;Fabrizio Sebastiani

  • Multi-facet Rating of Product Reviews

    Stefano Baccianella;Andrea Esuli;Fabrizio Sebastiani

  • CoPhIR: a Test Collection for Content-Based Image Retrieval

    Paolo Bolettieri;Andrea Esuli;Fabrizio Falchi;Claudio Lucchese

  • Fine-Grained Visual Textual Alignment for Cross-Modal Retrieval Using Transformer Encoders

    Nicola Messina;Giuseppe Amato;Andrea Esuli;Fabrizio Falchi

  • Determining the semantic orientation of terms through gloss analysis

    Andrea Esuli;Fabrizio Sebastiani

  • Boosting multi-label hierarchical text categorization

    Andrea Esuli;Tiziano Fagni;Fabrizio Sebastiani

  • Automatically Determining Attitude Type and Force for Sentiment Analysis

    Shlomo Argamon;Kenneth Bloom;Andrea Esuli;Fabrizio Sebastiani

  • Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining

    Diego Marcheggiani;Oscar Täckström;Andrea Esuli;Fabrizio Sebastiani

  • Distributional Random Oversampling for Imbalanced Text Classification

    Alejandro Moreo;Andrea Esuli;Fabrizio Sebastiani

  • Optimizing Text Quantifiers for Multivariate Loss Functions.

    Andrea Esuli;Fabrizio Sebastiani

  • Optimizing Text Quantifiers for Multivariate Loss Functions

    Andrea Esuli;Fabrizio Sebastiani

  • An NLP approach for cross-domain ambiguity detection in requirements engineering

    Alessio Ferrari;Andrea Esuli

  • Automatic Generation of Lexical Resources for Opinion Mining: Models, Algorithms and Applications

    Andrea Esuli

  • Active Learning Strategies for Multi-Label Text Classification

    Andrea Esuli;Fabrizio Sebastiani

  • Machines that learn how to code open-ended survey data

    Andrea Esuli;Fabrizio Sebastiani

  • AI and Opinion Mining, Part 2

    Andrea Esuli;Fabrizio Sebastiani;Ahmed Abasi

Frequent Co-Authors

Fabrizio Sebastiani
Fabrizio Sebastiani Institute of Information Science and Technologies
Chiara Renso
Chiara Renso Institute of Information Science and Technologies
Raffaele Perego
Raffaele Perego Institute of Information Science and Technologies
Claudio Lucchese
Claudio Lucchese Ca Foscari University of Venice
Alessio Ferrari
Alessio Ferrari École Polytechnique Fédérale de Lausanne
Giuseppe Amato
Giuseppe Amato Institute of Information Science and Technologies
Fabrizio Silvestri
Fabrizio Silvestri Sapienza University of Rome
Stefania Gnesi
Stefania Gnesi Institute of Information Science and Technologies
Iadh Ounis
Iadh Ounis University of Glasgow
Dino Pedreschi
Dino Pedreschi University of Pisa

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