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Computer Science
Italy
2025

D-Index & Metrics

Computer Science

D-Index
58
Citations
15992
World Ranking
3579
National Ranking
65

Stefano Nolfi 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 Stefano Nolfi 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: 235 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Stefano Nolfi 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 Stefano Nolfi 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: 58 D-Index — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Italy Leader Award
  • 2022 - Research.com Computer Science in Italy Leader Award

Overview

Stefano Nolfi is affiliated with the National Research Council (CNR) in Italy and has a significant body of work in the field of computer science, particularly focused on artificial intelligence.

Their research topics prominently cover:

  • Evolutionary Algorithms and Applications
  • Reinforcement Learning in Robotics
  • Metaheuristic Optimization Algorithms Research
  • Modular Robots and Swarm Intelligence
  • Action Observation and Synchronization
  • Topic Modeling
  • Natural Language Processing Techniques

Nolfi's publications span several key subfields, including artificial intelligence with a strong leaning toward robotics and machine learning, alongside contributions to mechanical engineering, social psychology, computer vision and pattern recognition, and cognitive neuroscience.

Their work appears frequently in specific venues, which include:

  • Frontiers in Robotics and AI
  • arXiv (Cornell University)
  • Adaptive Behavior
  • Evolutionary Intelligence
  • Artificial Life

Frequent coauthors in their research collaborations are:

  • Nicola Milano
  • Paolo Pagliuca
  • Jônata Tyska Carvalho
  • Fernando Aldana-Franco
  • Fernando Montes-González

Among recent publications, notable papers include:

  • "On the Unexpected Abilities of Large Language Models," 2024, Adaptive Behavior
  • "Improvement of Signal Communication for a Foraging Task Using Evolutionary Robotics," 2024, Journal of Applied Research and Technology
  • "The Role of Morphological Variation in Evolutionary Robotics: Maximizing Performance and Robustness," 2023, Evolutionary Computation
  • "Development of Multiple Behaviors in Evolving Robots," 2020, Robotics
  • "Efficacy of Modern Neuro-Evolutionary Strategies for Continuous Control Optimization," 2020, Frontiers in Robotics and AI

Their research contributions integrate themes of evolutionary computing applied to robotics, continuous control optimization, and behavior development in evolving systems. Their work on large language models suggests an interest also in emerging capabilities of artificial intelligence beyond traditional robotic applications.

Best Publications

  • Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines

    Stefano Nolfi;Dario Floreano

  • Evolutionary robotics

    Evert Haasdijk;Nicolas Bredeche;Stefano Nolfi;A. E. Eiben

  • Swarmanoid: A Novel Concept for the Study of Heterogeneous Robotic Swarms

    Marco Dorigo;Dario Floreano;Luca Maria Gambardella;Francesco Mondada

  • Evolving mobile robots in simulated and real environments

    Orazio Miglino;Henrik Hautop Lund;Stefano Nolfi

  • Swarm-Bot: A New Distributed Robotic Concept

    Francesco Mondada;Giovanni C. Pettinaro;Andre Guignard;Ivo W. Kwee

  • Learning and evolution in neural networks

    Stefano Nolfi;Domenico Parisi;Jeffrey L. Elman

  • Evolving Self-Organizing Behaviors for a Swarm-Bot

    Marco Dorigo;Vito Trianni;Erol Şahin;Roderich Groß

  • Learning to perceive the world as articulated: an approach for hierarchical learning in sensory-motor systems

    J. Tani;S. Nolfi

  • How to Evolve Autonomous Robots: Different Approaches in Evolutionary Robotics

    Stefano Nolfi;Dario Floreano;Orazio Miglino;Francesco Mondada

  • Coevolving Predator and Prey Robots: Do Arms Races Arise in Artificial Evolution?

    Stefano Nolfi;Dario Floreano

  • Learning to Adapt to Changing Environments in Evolving Neural Networks

    Stefano Nolfi;Domenico Parisi

  • The cooperation of swarm-bots: physical interactions in collective robotics

    F. Mondada;L.M. Gambardella;D. Floreano;S. Nolfi

  • Evolving mobile robots able to display collective behaviors

    Gianluca Baldassarre;Stefano Nolfi;Domenico Parisi

  • Learning and Evolution

    Stefano Nolfi;Dario Floreano

  • Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

    A Cangelosi;G Metta;G Sagerer;S Nolfi

  • Cell division and migration in a `genotype' for neural networks

    Angelo Cangelosi;Domenico Parisi;Stefano Nolfi

  • Econets: Neural networks that learn in an environment

    Domenico Parisi;Federico Cecconi;Stefano Nolfi

  • Evolving non-trivial behaviors on real robots: A garbage collecting robot

    Stefano Nolfi

  • Using emergent modularity to develop control systems for mobile robots

    Stefano Nolfi

  • The SWARM-BOTS project

    Marco Dorigo;Elio Tuci;Roderich Groß;Vito Trianni

  • Co-evolving predator and prey robots

    Stefano Nolfi

  • Cell division and migration in a 'genotype' for neural networks (Cell division and migration in neural networks)

    Angelo Cangelosi;Domenico Parisi;Stefano Nolfi

Frequent Co-Authors

Domenico Parisi
Domenico Parisi National Academies of Sciences, Engineering, and Medicine
Marco Dorigo
Marco Dorigo Université Libre de Bruxelles
Vito Trianni
Vito Trianni National Research Council (CNR)
Francesco Mondada
Francesco Mondada École Polytechnique Fédérale de Lausanne
Luca Maria Gambardella
Luca Maria Gambardella Dalle Molle Institute for Artificial Intelligence Research
Gianluca Baldassarre
Gianluca Baldassarre National Academies of Sciences, Engineering, and Medicine
Angelo Cangelosi
Angelo Cangelosi University of Manchester
Jean-Louis Deneubourg
Jean-Louis Deneubourg Université Libre de Bruxelles
Jun Tani
Jun Tani Okinawa Institute of Science and Technology
Katharina J. Rohlfing
Katharina J. Rohlfing University of Paderborn

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