World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
6820
World Ranking
10625
National Ranking
330

Paola Velardi 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 Paola Velardi 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: 165 publications — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Paola Velardi 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 Paola Velardi 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Paola Velardi is affiliated with Sapienza University of Rome in Italy. Their research spans significant areas within computer science and biochemistry, genetics, and molecular biology, with a total of 49 publications in computer science and 23 in biochemistry and related fields.

The main subfields of study in their work include:

  • Artificial Intelligence
  • Molecular Biology
  • Computer Vision and Pattern Recognition
  • Communication
  • Computer Science Applications

Their research covers an array of interconnected topics, such as:

  • Bioinformatics and Genomic Networks
  • Biomedical Text Mining and Ontologies
  • Anomaly Detection Techniques and Applications
  • Data Stream Mining Techniques
  • Time Series Analysis and Forecasting
  • Computational Drug Discovery Methods
  • Gene expression and cancer classification

Notable recent papers authored or coauthored by Paola Velardi include:

  • A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses, 2020, ACM Computing Surveys
  • Assessment of community efforts to advance network-based prediction of protein-protein interactions, 2023, Nature Communications
  • Gender, rank, and social networks on an enterprise social media platform, 2020, Social Networks
  • Hidden space deep sequential risk prediction on student trajectories, 2021, Future Generation Computer Systems
  • A self-supervised algorithm to detect signs of social isolation in the elderly from daily activity sequences, 2022, Artificial Intelligence in Medicine

Velardi has collaborated frequently with several researchers, the most common coauthors being:

  • Bardh Prenkaj
  • Lorenzo Madeddu
  • Stefano Faralli
  • Luca Podo
  • Giovanni Stilo

Their research has appeared regularly in certain venues, including:

  • arXiv (Cornell University)
  • International Journal of Data Mining and Bioinformatics
  • Applied Sciences
  • SSRN Electronic Journal
  • ACM Computing Surveys

Best Publications

  • Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites

    Roberto Navigli;Paola Velardi

  • Ontology learning and its application to automated terminology translation

    R. Navigli;P. Velardi;A. Gangemi

  • Structural semantic interconnections: a knowledge-based approach to word sense disambiguation

    R. Navigli;P. Velardi

  • Using text processing techniques to automatically enrich a domain ontology

    Paola Velardi;Paolo Fabriani;Michele Missikoff

  • An analysis of ontology-based query expansion strategies

    Paola Velardi;R Navigli

  • TermExtractor: a Web Application to Learn the Shared Terminology of Emergent Web Communities

    F. Sclano;Paola Velardi

  • The OntoWordNet Project: Extension and Axiomatization of Conceptual Relations in WordNet

    Aldo Gangemi;Roberto Navigli;Paola Velardi

  • Integrated approach to Web ontology learning and engineering

    M. Missikoff;R. Navigli;P. Velardi

  • OntoLearn Reloaded: A Graph-Based Algorithm for Taxonomy Induction

    Paola Velardi;Stefano Faralli;Roberto Navigli

  • Learning Word-Class Lattices for Definition and Hypernym Extraction

    Roberto Navigli;Paola Velardi

  • A graph-based algorithm for inducing lexical taxonomies from scratch

    Roberto Navigli;Paola Velardi;Stefano Faralli

  • Evaluation of OntoLearn, a Methodology for Automatic Learning of Domain Ontologies

    Paola Velardi;Roberto Navigli;A Cucchiarelli;F Neri

  • Identification of relevant terms to support the construction of domain ontologies

    Paola Velardi;Michele Missikoff;Roberto Basili

  • The Usable Ontology: An Environment for Building and Assessing a Domain Ontology

    Michele Missikoff;Roberto Navigli;Paola Velardi

  • Hardware-Related Software Errors: Measurement and Analysis

    R.K. Iyer;P. Velardi

  • A Taxonomy Learning Method and Its Application to Characterize a Scientific Web Community

    P. Velardi;A. Cucchiarelli;M. Petit

  • Twitter mining for fine-grained syndromic surveillance

    Paola Velardi;Giovanni Stilo;Alberto E. Tozzi;Francesco Gesualdo

  • Unsupervised named entity recognition using syntactic and semantic contextual evidence

    Alessandro Cucchiarelli;Paola Velardi

  • A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses

    Bardh Prenkaj;Paola Velardi;Giovanni Stilo;Damiano Distante

  • How to encode semantic knowledge: a method for meaning representation and computer-aided acquisition

    Paola Velardi;Michela Fasolo;Maria Teresa Pazienza

  • Structural semantic interconnection: a knowledge-based approach to Word Sense Disambiguation

    Roberto Navigli;Paola Velardi

Frequent Co-Authors

Roberto Navigli
Roberto Navigli Sapienza University of Rome
Roberto Basili
Roberto Basili University of Rome Tor Vergata
Simone Paolo Ponzetto
Simone Paolo Ponzetto University of Mannheim
Aldo Gangemi
Aldo Gangemi University of Bologna
Nada Lavrač
Nada Lavrač Jozef Stefan Institute
Alessandro Vespignani
Alessandro Vespignani Northeastern University
Roni Rosenfeld
Roni Rosenfeld Carnegie Mellon University
Mark Dredze
Mark Dredze Johns Hopkins University
Alessandro Fiocchi
Alessandro Fiocchi Bambino Gesù Children's Hospital
Lyn Finelli
Lyn Finelli Centers for Disease Control and Prevention

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