World's Best Scientists 2026 revealed!
Davide Anguita

Davide Anguita

D-Index & Metrics

Computer Science

D-Index
41
Citations
9933
World Ranking
8667
National Ranking
237

Davide Anguita 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 Davide Anguita 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: 223 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

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

Davide Anguita 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 Davide Anguita 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Davide Anguita is affiliated with the University of Genoa in Italy. Their research contributions span multiple topics within computer science and engineering, with a focus on artificial intelligence, computer vision, and control systems.

The scientist has published extensively in several frequent venues, including:

  • Neurocomputing
  • Cognitive Computation
  • 2022 International Joint Conference on Neural Networks (IJCNN)
  • ESANN 2021 proceedings
  • arXiv (Cornell University)

Their recent publications include the following papers:

  • "JUCS - Journal of Universal Computer Science," 2020, CINECA IRIS Institutional research information system (University of Pisa)
  • "Bridging Cognitive Models and Recommender Systems," 2020, Cognitive Computation
  • "Understanding Violin Players' Skill Level Based on Motion Capture: a Data-Driven Perspective," 2020, Cognitive Computation
  • "Optimizing Fuel Consumption in Thrust Allocation for Marine Dynamic Positioning Systems," 2021, IEEE Transactions on Automation Science and Engineering
  • "Deep fair models for complex data: Graphs labeling and explainable face recognition," 2021, Neurocomputing

Frequent co-authors working alongside Davide Anguita include:

  • Luca Oneto
  • Sandro Ridella
  • Antonio Camurri
  • Andrea Coraddu
  • Nicolò Navarin

The main fields of study for their work cover:

  • Computer Science
  • Engineering

Subfields within these areas include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Safety Research

Their research topics reveal interests in several specialized areas evidenced by publication coverage:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Ethics and Social Impacts of AI
  • Explainable Artificial Intelligence (XAI)
  • Fault Detection and Control Systems
  • Neuroscience and Music Perception
  • Maritime Navigation and Safety

Best Publications

  • A public domain dataset for human activity recognition using smartphones

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • Transition-Aware Human Activity Recognition Using Smartphones

    Jorge-L. Reyes-Ortiz;Luca Oneto;Albert Samà;Xavier Parra

  • A digital architecture for support vector machines: theory, algorithm, and FPGA implementation

    D. Anguita;A. Boni;S. Ridella

  • Big Data Analytics in the Cloud: Spark on Hadoop vs MPI/OpenMP on Beowulf

    Jorge Luis Reyes-Ortiz;Luca Oneto;Davide Anguita

  • Energy Load Forecasting Using Empirical Mode Decomposition and Support Vector Regression

    L. Ghelardoni;A. Ghio;D. Anguita

  • Energy Efficient Smartphone-Based Activity Recognition Using Fixed-Point Arithmetic

    Davide Anguita;Alessandro Ghio;Luca Oneto;Xavier Parra

  • The 'K' in K-fold Cross Validation

    Davide Anguita;Luca Ghelardoni;Alessandro Ghio;Luca Oneto

  • Vessels fuel consumption forecast and trim optimisation: A data analytics perspective

    Andrea Coraddu;Luca Oneto;Francesco Baldi;Davide Anguita

  • Machine learning approaches for improving condition-based maintenance of naval propulsion plants

    Andrea Coraddu;Luca Oneto;Alessandro Ghio;Stefano Savio

  • Condition Based Maintenance in Railway Transportation Systems Based on Big Data Streaming Analysis

    Emanuele Fumeo;Luca Oneto;Davide Anguita

  • Train Delay Prediction Systems: A Big Data Analytics Perspective ☆

    Luca Oneto;Emanuele Fumeo;Giorgio Clerico;Renzo Canepa

  • In-Sample and Out-of-Sample Model Selection and Error Estimation for Support Vector Machines

    D. Anguita;A. Ghio;L. Oneto;S. Ridella

  • Quantum optimization for training support vector machines

    Davide Anguita;Sandro Ridella;Fabio Rivieccio;Rodolfo Zunino

  • Model selection for support vector machines: Advantages and disadvantages of the Machine Learning Theory

    Davide Anguita;Alessandro Ghio;Noemi Greco;Luca Oneto

  • K-Fold Cross Validation for Error Rate Estimate in Support Vector Machines.

    Davide Anguita;Alessandro Ghio;Sandro Ridella;Dario Sterpi

  • Statistical Learning Theory and ELM for Big Social Data Analysis

    Luca Oneto;Federica Bisio;Erik Cambria;Davide Anguita

  • Theoretical and Practical Model Selection Methods for Support Vector Classifiers

    Davide Anguita;Andrea Boni;Sandro Ridella;Fabio Rivieccio

  • Dynamic Delay Predictions for Large-Scale Railway Networks: Deep and Shallow Extreme Learning Machines Tuned via Thresholdout

    Luca Oneto;Emanuele Fumeo;Giorgio Clerico;Renzo Canepa

  • Human Activity Recognition on Smartphones with Awareness of Basic Activities and Postural Transitions

    Jorge Luis Reyes-Ortiz;Jorge Luis Reyes-Ortiz;Luca Oneto;Alessandro Ghio;Albert Samà

  • Building an Underwater Wireless Sensor Network Based on Optical: Communication: Research Challenges and Current Results

    Davide Anguita;Davide Brizzolara;Giancarlo Parodi

Frequent Co-Authors

Luca Oneto
Luca Oneto University of Genoa
Matthias Rauterberg
Matthias Rauterberg Eindhoven University of Technology
Erik Cambria
Erik Cambria Nanyang Technological University
Alessandro Sperduti
Alessandro Sperduti University of Padua
Antonio Camurri
Antonio Camurri University of Genoa
Salvatore Caorsi
Salvatore Caorsi University of Pavia
Rui Calçada
Rui Calçada University of Porto
Massimo Donelli
Massimo Donelli University of Trento
Federico Delfino
Federico Delfino University of Genoa
Maurizio Valle
Maurizio Valle University of Genoa

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