World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
70
Citations
19902
World Ranking
1028
National Ranking
30

Neuroscience

D-Index
79
Citations
21920
World Ranking
1686
National Ranking
152

Stefano Panzeri publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Stefano Panzeri sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 323 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Stefano Panzeri D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Stefano Panzeri sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 70 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Stefano Panzeri is affiliated with the Italian Institute of Technology in Italy and specializes in Neuroscience, with a significant focus on Cognitive Neuroscience, Cellular and Molecular Neuroscience, and aspects of Artificial Intelligence and Electrical and Electronic Engineering. Their research spans multiple domains within neuroscience, emphasizing neural dynamics and brain function.

The scientist's publication record includes work in prominent journals and repositories such as bioRxiv (Cold Spring Harbor Laboratory), eLife, Current Biology, Nature Communications, and arXiv (Cornell University). The volume of publications in these venues demonstrates sustained contributions to the field over time.

Key topics covered in their research include:

  • Neural dynamics and brain function
  • Functional Brain Connectivity Studies
  • EEG and Brain-Computer Interfaces
  • Neuroscience and Neural Engineering
  • Neuroscience and Neuropharmacology Research
  • Photoreceptor and optogenetics research
  • Advanced Memory and Neural Computing

Frequent collaborators in their research activity include Tommaso Fellin, Marco Celotto, Pablo Martínez-Cañada, Cristina Becchio, and Monica Moroni, reflecting active engagement within a research community.

Recent scholarly contributions include the following papers:

  • The structures and functions of correlations in neural population codes, 2022, published in Nature Reviews. Neuroscience
  • Structure and flexibility in cortical representations of odour space, 2020, published in Nature
  • Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women, 2020, published in eLife
  • Testing theory of mind in large language models and humans, 2024, published in Nature Human Behaviour
  • Manipulating synthetic optogenetic odors reveals the coding logic of olfactory perception, 2020, published in Science

Best Publications

  • Extracting information from neuronal populations: information theory and decoding approaches.

    Rodrigo Quian Quiroga;Stefano Panzeri;Stefano Panzeri

  • Modelling and analysis of local field potentials for studying the function of cortical circuits

    Gaute T. Einevoll;Christoph Kayser;Nikos K. Logothetis;Stefano Panzeri

  • Speech rhythms and multiplexed oscillatory sensory coding in the human brain.

    Joachim Gross;Nienke Hoogenboom;Gregor Thut;Philippe G. Schyns

  • Sensory neural codes using multiplexed temporal scales

    Stefano Panzeri;Nicolas Brunel;Nicolas Brunel;Nikos K. Logothetis;Nikos K. Logothetis;Christoph Kayser

  • Spike-phase coding boosts and stabilizes information carried by spatial and temporal spike patterns.

    Christoph Kayser;Marcelo A. Montemurro;Nikos K. Logothetis;Nikos K. Logothetis;Stefano Panzeri;Stefano Panzeri

  • The Role of Spike Timing in the Coding of Stimulus Location in Rat Somatosensory Cortex

    Stefano Panzeri;Rasmus S. Petersen;Simon R. Schultz;Michael Lebedev

  • Correcting for the Sampling Bias Problem in Spike Train Information Measures

    Stefano Panzeri;Riccardo Senatore;Marcelo A. Montemurro;Rasmus S. Petersen

  • Analytical estimates of limited sampling biases in different information measures.

    Stefano Panzeri;Alessandro Treves

  • Low-frequency local field potentials and spikes in primary visual cortex convey independent visual information.

    Andrei Belitski;Arthur Gretton;Cesare Magri;Yusuke Murayama

  • Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models.

    Alberto Mazzoni;Alberto Mazzoni;Henrik Lindén;Henrik Lindén;Hermann Cuntz;Hermann Cuntz;Hermann Cuntz;Anders Lansner

  • The upward bias in measures of information derived from limited data samples

    Alessandro Treves;Stefano Panzeri

  • Phase-of-Firing Coding of Natural Visual Stimuli in Primary Visual Cortex

    Marcelo A. Montemurro;Malte J. Rasch;Yusuke Murayama;Nikos K. Logothetis;Nikos K. Logothetis

  • Correlations and the encoding of information in the nervous system

    Stefano Panzeri;Simon R. Schultz;Alessandro Treves;Edmund T. Rolls

  • Distinct timescales of population coding across cortex

    Caroline A. Runyan;Eugenio Piasini;Stefano Panzeri;Christopher D. Harvey

  • The threshold for conscious report: Signal loss and response bias in visual and frontal cortex

    Bram van Vugt;Bruno Dagnino;Devavrat Vartak;Houman Safaai;Houman Safaai

  • The Amplitude and Timing of the BOLD Signal Reflects the Relationship between Local Field Potential Power at Different Frequencies

    Cesare Magri;Ulrich Schridde;Yusuke Murayama;Stefano Panzeri

  • Encoding of Naturalistic Stimuli by Local Field Potential Spectra in Networks of Excitatory and Inhibitory Neurons

    Alberto Mazzoni;Stefano Panzeri;Nikos K. Logothetis;Nicolas Brunel;Nicolas Brunel

  • Population coding of stimulus location in rat somatosensory cortex.

    Rasmus S. Petersen;Stefano Panzeri;Mathew E. Diamond

  • The Neurophysiology of Backward Visual Masking: Information Analysis

    Edmund T. Rolls;Martin J. Tovée;Stefano Panzeri

  • The structures and functions of correlations in neural population codes

    Unknown

  • A toolbox for the fast information analysis of multiple-site LFP, EEG and spike train recordings

    Cesare Magri;Kevin Whittingstall;Vanessa Singh;Nikos K Logothetis;Nikos K Logothetis

Frequent Co-Authors

Nikos K. Logothetis
Nikos K. Logothetis Chinese Academy of Sciences
Christoph Kayser
Christoph Kayser Bielefeld University
Mathew E. Diamond
Mathew E. Diamond International School for Advanced Studies
Thierry Pozzo
Thierry Pozzo Italian Institute of Technology
Alessandro Treves
Alessandro Treves International School for Advanced Studies
Tommaso Fellin
Tommaso Fellin Italian Institute of Technology
Edmund T. Rolls
Edmund T. Rolls University of Warwick
Nicolas Brunel
Nicolas Brunel Duke University
Philippe G. Schyns
Philippe G. Schyns University of Glasgow
Gaute T. Einevoll
Gaute T. Einevoll Norwegian University of Life Sciences

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