World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
4092
World Ranking
13668
National Ranking
495

Claudio Lucchese 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 Claudio Lucchese 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: 178 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Claudio Lucchese 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 Claudio Lucchese 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

Claudio Lucchese is affiliated with Ca Foscari University of Venice in Italy. Their research predominantly lies within the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Signal Processing, Safety Research, Management Science and Operations Research, and Information Systems.

The scientist's work spans multiple topics, notably Adversarial Robustness in Machine Learning, Explainable Artificial Intelligence (XAI), Advanced Malware Detection Techniques, Machine Learning and Data Classification, Ethics and Social Impacts of AI, Anomaly Detection Techniques and Applications, and Security and Verification in Computing.

Claudio Lucchese has contributed to numerous publications across various venues. Some of the frequent publication outlets include:

  • arXiv (Cornell University)
  • Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
  • Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • ACM Transactions on Information Systems
  • IRIS Research product catalog (Sapienza University of Rome)

Recent papers authored or co-authored by Claudio Lucchese are:

  • "Treant: training evasion-aware decision trees", 2020, Data Mining and Knowledge Discovery
  • "Treant: training evasion-aware decision trees", 2020, IRIS Research product catalog (Sapienza University of Rome)
  • "Efficient and Effective Tree-based and Neural Learning to Rank", 2023, Foundations and Trends® in Information Retrieval
  • "ReNeuIR: Reaching Efficiency in Neural Information Retrieval", 2022, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  • "Beyond robustness: Resilience verification of tree-based classifiers", 2022, Computers & Security

Collaboration appears to be an important aspect of Lucchese's research activities, with frequent co-authors including Salvatore Orlando, Franco Maria Nardini, Stefano Calzavara, Federico Marcuzzi, and Raffaele Perego.

Best Publications

  • Fast and memory efficient mining of frequent closed itemsets

    C. Lucchese;S. Orlando;R. Perego

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

    Paolo Bolettieri;Andrea Esuli;Fabrizio Falchi;Claudio Lucchese

  • From chatter to headlines: harnessing the real-time web for personalized news recommendation

    Gianmarco De Francisci Morales;Aristides Gionis;Claudio Lucchese

  • Identifying task-based sessions in search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • Building a web-scale image similarity search system

    Michal Batko;Fabrizio Falchi;Claudio Lucchese;David Novak

  • Document Similarity Self-Join with MapReduce

    Ranieri Baraglia;Gianmarco De Francisci Morales;Claudio Lucchese

  • On closed constrained frequent pattern mining

    F. Bonchi;C. Lucchese

  • Learning relatedness measures for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • Direct local pattern sampling by efficient two-step random procedures

    Mario Boley;Claudio Lucchese;Daniel Paurat;Thomas Gärtner

  • Pushing tougher constraints in frequent pattern mining

    Francesco Bonchi;Claudio Lucchese

  • Extending the state-of-the-art of constraint-based pattern discovery

    Francesco Bonchi;Claudio Lucchese

  • kDCI: a Multi-Strategy Algorithm for Mining Frequent Sets.

    Salvatore Orlando;Claudio Lucchese;Paolo Palmerini;Raffaele Perego

  • Fast Ranking with Additive Ensembles of Oblivious and Non-Oblivious Regression Trees

    Domenico Dato;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Dexter: an open source framework for entity linking

    Diego Ceccarelli;Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • QuickScorer: A Fast Algorithm to Rank Documents with Additive Ensembles of Regression Trees

    Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando;Raffaele Perego

  • Discovering tasks from search engine query logs

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego;Fabrizio Silvestri

  • DCI_Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets

    Claudio Lucchese;Salvatore Orlando;R. Perego

  • Quality versus efficiency in document scoring with learning-to-rank models

    Gabriele Capannini;Claudio Lucchese;Franco Maria Nardini;Salvatore Orlando

  • Mining Top-K Patterns from Binary Datasets in presence of Noise

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • A Unifying Framework for Mining Approximate Top-k Binary Patterns

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

  • DCI Closed: A Fast and Memory Efficient Algorithm to Mine Frequent Closed Itemsets.

    Claudio Lucchese;Salvatore Orlando;Raffaele Perego

Frequent Co-Authors

Raffaele Perego
Raffaele Perego Institute of Information Science and Technologies
Salvatore Orlando
Salvatore Orlando Ca Foscari University of Venice
Fabrizio Silvestri
Fabrizio Silvestri Sapienza University of Rome
Francesco Bonchi
Francesco Bonchi Institute for Scientific Interchange
Michail Vlachos
Michail Vlachos University of Lausanne
Chiara Renso
Chiara Renso Institute of Information Science and Technologies
Andrea Esuli
Andrea Esuli Institute of Information Science and Technologies
Fosca Giannotti
Fosca Giannotti Scuola Normale Superiore di Pisa
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Aristides Gionis
Aristides Gionis Royal Institute of Technology

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