World's Best Scientists 2026 revealed!
Alessandro Sperduti

Alessandro Sperduti

D-Index & Metrics

Computer Science

D-Index
43
Citations
8790
World Ranking
7911
National Ranking
206

Alessandro Sperduti 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 Alessandro Sperduti 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: 291 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Alessandro Sperduti 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 Alessandro Sperduti 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Alessandro Sperduti is affiliated with the University of Padua in Italy and specializes primarily in Computer Science, with a focus on Artificial Intelligence. Their academic contributions prominently span the subfields of Computer Vision and Pattern Recognition, Molecular Biology, Computational Theory and Mathematics, and Statistical and Nonlinear Physics.

The research topics covered in their work include Advanced Graph Neural Networks, Neural Networks and Applications, Domain Adaptation and Few-Shot Learning, Complex Network Analysis Techniques, Computational Drug Discovery Methods, Multimodal Machine Learning Applications, and Neural Networks and Reservoir Computing.

Sperduti has published extensively in various venues, frequently contributing to:

  • arXiv (Cornell University)
  • Neurocomputing
  • Neural Computing and Applications
  • IEEE Computational Intelligence Magazine
  • Nature

Some of the recent papers associated with this researcher include:

  • "Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo'" (2020, Nature)
  • "Suppression of COVID-19 outbreak in the municipality of Vo', Italy" (2020, bioRxiv - Cold Spring Harbor Laboratory)
  • "Multi-task learning for the prediction of wind power ramp events with deep neural networks" (2020, Neural Networks)
  • "Conditional Variational Capsule Network for Open Set Recognition" (2021, 2021 IEEE/CVF International Conference on Computer Vision - ICCV)
  • "Multiresolution Reservoir Graph Neural Network" (2021, IEEE Transactions on Neural Networks and Learning Systems)

Frequent collaborative relationships have been established with researchers including:

  • Nicolò Navarin
  • Luca Pasa
  • Davide Rigoni
  • Luciano Serafini
  • Alberto Testolin

Best Publications

  • Process Mining Manifesto

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

  • Supervised neural networks for the classification of structures

    A. Sperduti;A. Starita

  • A general framework for adaptive processing of data structures

    P. Frasconi;M. Gori;A. Sperduti

  • A self-organizing map for adaptive processing of structured data

    M. Hagenbuchner;A. Sperduti;Ah Chung Tsoi

  • Conformance checking based on multi-perspective declarative process models

    Andrea Burattin;Fabrizio M. Maggi;Alessandro Sperduti

  • Speed up learning and network optimization with extended back propagation

    Alessandro Sperduti;Antonina Starita

  • Time and activity sequence prediction of business process instances

    Mirko Polato;Alessandro Sperduti;Andrea Burattin;Massimiliano de Leoni

  • Recursive self-organizing network models

    Barbara Hammer;Alessio Micheli;Alessandro Sperduti;Marc Strickert

  • A general framework for unsupervised processing of structured data

    Barbara Hammer;Alessio Micheli;Alessandro Sperduti;Marc Strickert

  • ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications

    Hossein Fereidooni;Mauro Conti;Danfeng Yao;Alessandro Sperduti

  • An improved boosting algorithm and its application to text categorization

    Fabrizio Sebastiani;Alessandro Sperduti;Nicola Valdambrini

  • Data-aware remaining time prediction of business process instances

    M Polato;A Sperduti;A Burattin;de M Massimiliano Leoni

  • Application of Cascade Correlation Networks for Structures toChemistry

    Anna Maria Bianucci;Alessio Micheli;Alessandro Sperduti;Antonina Starita

  • LSTM networks for data-aware remaining time prediction of business process instances

    Nicolo Navarin;Beatrice Vincenzi;Mirko Polato;Alessandro Sperduti

  • PLG: a Framework for the Generation of Business Process Models and their Execution Logs

    Andrea Burattin;Alessandro Sperduti

  • Analysis of the internal representations developed by neural networks for structures applied to quantitative structure--activity relationship studies of benzodiazepines.

    Alessio Micheli;Alessandro Sperduti;Antonina Starita;Anna Maria Bianucci

  • Multiclass Classification with Multi-Prototype Support Vector Machines

    Fabio Aiolli;Alessandro Sperduti

  • Control-flow discovery from event streams

    Andrea Burattin;Alessandro Sperduti;Wil M. P. van der Aalst

  • Logo Recognition by Recursive Neural Networks

    Enrico Francesconi;Paolo Frasconi;Marco Gori;Simone Marinai

  • Heuristics miners for streaming event data

    A Burattin;A Sperduti;van der Wmp Wil Aalst

  • Multi-task learning for the prediction of wind power ramp events with deep neural networks.

    Manuel Dorado-Moreno;Nicolò Navarin;Nicolò Navarin;Pedro Antonio Gutiérrez;Luis Prieto

Frequent Co-Authors

Alessio Micheli
Alessio Micheli University of Pisa
Marco Gori
Marco Gori University of Siena
Ah Chung Tsoi
Ah Chung Tsoi University of Wollongong
Barbara Hammer
Barbara Hammer Bielefeld University
Francesca Rossi
Francesca Rossi IBM (United States)
Paolo Frasconi
Paolo Frasconi University of Florence
Wil M. P. van der Aalst
Wil M. P. van der Aalst RWTH Aachen University
Fabrizio Maria Maggi
Fabrizio Maria Maggi Free University of Bozen-Bolzano
Andrea Crisanti
Andrea Crisanti University of Padua
Christl A. Donnelly
Christl A. Donnelly University of Oxford

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