World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
9301
World Ranking
7145
National Ranking
176

Donato Malerba 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 Donato Malerba 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: 398 publications — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Donato Malerba 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 Donato Malerba 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Donato Malerba is affiliated with the University of Bari Aldo Moro in Italy and has published extensively in the field of Computer Science, with a particular focus on Artificial Intelligence and related subfields. Their research encompasses several areas including Computer Networks and Communications, Signal Processing, Media Technology, and Ecology.

Their main research topics include:

  • Network Security and Intrusion Detection
  • Anomaly Detection Techniques and Applications
  • Advanced Malware Detection Techniques
  • Data Stream Mining Techniques
  • Adversarial Robustness in Machine Learning
  • Remote-Sensing Image Classification
  • Internet Traffic Analysis and Secure E-voting

Malerba's recent scholarly papers demonstrate a concentration on network intrusion detection and deep learning methodologies. Among their published works are:

  • Autoencoder-based deep metric learning for network intrusion detection, 2021, published in Information Sciences
  • Multi-Channel Deep Feature Learning for Intrusion Detection, 2020, published in IEEE Access
  • GAN augmentation to deal with imbalance in imaging-based intrusion detection, 2021, published in Future Generation Computer Systems
  • Nearest cluster-based intrusion detection through convolutional neural networks, 2021, published in Knowledge-Based Systems
  • A Multi-View Deep Learning Approach for Predictive Business Process Monitoring, 2021, published in IEEE Transactions on Services Computing

The scientist has collaborated frequently with several co-authors, most notably Annalisa Appice, Giuseppina Andresini, Vincenzo Pasquadibisceglie, Corrado Appice Annalisa Malerba Donato Loglisci, and Giovanna Castellano. These collaborations have contributed to a substantial body of work across related domains.

Publication venues where Malerba's work appears recurrently include:

  • Journal of Intelligent Information Systems
  • IEEE Transactions on Services Computing
  • IEEE Access
  • Expert Systems with Applications
  • Engineering Applications of Artificial Intelligence

In addition to journal articles, the scientist has contributed to book publications, including work published by Springer Science+Business Media. One such publication is the ECML PKDD 2020 Workshops volume released in 2020.

Best Publications

  • Process Mining Manifesto

    Wil van der Aalst;Wil van der Aalst;Arya Adriansyah;Ana Karla Alves de Medeiros;Franco Arcieri

  • A comparative analysis of methods for pruning decision trees

    F. Esposito;D. Malerba;G. Semeraro;J. Kay

  • Transforming paper documents into XML format with WISDOM

    Oronzo Altamura;Floriana Esposito;Donato Malerba

  • A logic framework for the incremental inductive synthesis of Datalog theories

    G. Semeraro;F. Esposito;D. Malerba;N. Fanizzi

  • Inducing Multi-Level Association Rules from Multiple Relations

    Francesca A. Lisi;Donato Malerba

  • Classifying web documents in a hierarchy of categories: a comprehensive study

    Michelangelo Ceci;Donato Malerba

  • Autoencoder-based deep metric learning for network intrusion detection

    Giuseppina Andresini;Annalisa Appice;Donato Malerba

  • Discovery of spatial association rules in geo-referenced census data: A relational mining approach

    Annalisa Appice;Michelangelo Ceci;Antonietta Lanza;Francesca A. Lisi

  • Top-down induction of model trees with regression and splitting nodes

    D. Malerba;F. Esposito;M. Ceci;A. Appice

  • GAN augmentation to deal with imbalance in imaging-based intrusion detection

    Giuseppina Andresini;Annalisa Appice;Luca De Rose;Donato Malerba

  • MULTISTRATEGY LEARNING FOR DOCUMENT RECOGNITION

    Floriana Esposito;Donato Malerba;Giovanni Semeraro

  • Multi-Channel Deep Feature Learning for Intrusion Detection

    Giuseppina Andresini;Annalisa Appice;Nicola Di Mauro;Corrado Loglisci

  • Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction?

    Michelangelo Ceci;Roberto Corizzo;Fabio Fumarola;Donato Malerba

  • Using Convolutional Neural Networks for Predictive Process Analytics

    Vincenzo Pasquadibisceglie;Annalisa Appice;Giovanna Castellano;Donato Malerba

  • Nearest cluster-based intrusion detection through convolutional neural networks

    Giuseppina Andresini;Annalisa Appice;Donato Malerba

  • CloFAST: closed sequential pattern mining using sparse and vertical id-lists

    Fabio Fumarola;Pasqua Fabiana Lanotte;Michelangelo Ceci;Donato Malerba

  • An experimental page layout recognition system for office document automatic classification: an integrated approach for inductive generalization

    F. Esposito;D. Malerba;G. Semeraro;E. Annese

  • Mining spatial association rules in census data

    Donato Malerba;Floriana Esposito;Francesca A. Lisi;Annalisa Appice

  • Machine learning methods for automatically processing historical documents: from paper acquisition to XML transformation

    F. Esposito;D. Malerba;G. Semeraro;S. Ferilli

  • A Co-Training Strategy for Multiple View Clustering in Process Mining

    Annalisa Appice;Donato Malerba

  • Completion Time and Next Activity Prediction of Processes Using Sequential Pattern Mining

    Michelangelo Ceci;Pasqua Fabiana Lanotte;Fabio Fumarola;Dario Pietro Cavallo

  • Comparing Dissimilarity Measures for Symbolic Data Analysis

    Donato Malerba;Floriana Esposito;Vincenzo Gioviale;Valentina Tamma

Frequent Co-Authors

Annalisa Appice
Annalisa Appice University of Bari Aldo Moro
Michelangelo Ceci
Michelangelo Ceci University of Bari Aldo Moro
Floriana Esposito
Floriana Esposito University of Bari Aldo Moro
Giovanni Semeraro
Giovanni Semeraro University of Bari Aldo Moro
Giovanna Castellano
Giovanna Castellano University of Bari Aldo Moro
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Dimitrios Gunopulos
Dimitrios Gunopulos National and Kapodistrian University of Athens
Michalis Vazirgiannis
Michalis Vazirgiannis École Polytechnique
Sašo Džeroski
Sašo Džeroski Jožef Stefan Institute
Alfredo Cuzzocrea
Alfredo Cuzzocrea University of Calabria

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