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James J. DiCarlo

James J. DiCarlo

MIT
United States

D-Index & Metrics

Neuroscience

D-Index
68
Citations
45434
World Ranking
2691
National Ranking
1261

James J. DiCarlo publication distribution in Neuroscience in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Neuroscience in 2026. The highlighted bar marks where James J. DiCarlo sits on this spectrum.

38–47 publications: 18 scientists 48–57 publications: 79 scientists 58–67 publications: 193 scientists 68–77 publications: 323 scientists 78–87 publications: 406 scientists 88–97 publications: 452 scientists 98–107 publications: 539 scientists 108–117 publications: 505 scientists 118–127 publications: 522 scientists 128–137 publications: 469 scientists 138–147 publications: 456 scientists 148–157 publications: 459 scientists 158–167 publications: 397 scientists 168–177 publications: 383 scientists 178–187 publications: 350 scientists 188–197 publications: 302 scientists 198–207 publications: 306 scientists 208–217 publications: 262 scientists 218–227 publications: 242 scientists 228–237 publications: 220 scientists 238–247 publications: 203 scientists 248–257 publications: 174 scientists 258–267 publications: 176 scientists 268–277 publications: 175 scientists 278–287 publications: 125 scientists 288–297 publications: 116 scientists 298–307 publications: 127 scientists 308–317 publications: 128 scientists 318–327 publications: 99 scientists 328–337 publications: 89 scientists 338–347 publications: 78 scientists 348–357 publications: 96 scientists 358–367 publications: 66 scientists 368–377 publications: 59 scientists 378–387 publications: 65 scientists 388–397 publications: 54 scientists 398–407 publications: 48 scientists 408–417 publications: 49 scientists 418–427 publications: 34 scientists 428–437 publications: 31 scientists 438–447 publications: 30 scientists 448–457 publications: 31 scientists 458–467 publications: 36 scientists 468–477 publications: 40 scientists 478–487 publications: 35 scientists 488–497 publications: 30 scientists 498–507 publications: 23 scientists 508–517 publications: 26 scientists 518–527 publications: 20 scientists 528–537 publications: 23 scientists 538–547 publications: 20 scientists 548–557 publications: 20 scientists 558–567 publications: 17 scientists 568–577 publications: 14 scientists 578–587 publications: 20 scientists 588–597 publications: 20 scientists 598–607 publications: 19 scientists 608–617 publications: 18 scientists 618–627 publications: 17 scientists 628–637 publications: 11 scientists 638–647 publications: 11 scientists 648–657 publications: 11 scientists 658–667 publications: 8 scientists 668–677 publications: 7 scientists 678–687 publications: 11 scientists 688–697 publications: 10 scientists 698–707 publications: 4 scientists 708–717 publications: 6 scientists 718–727 publications: 5 scientists 728–737 publications: 5 scientists 738–747 publications: 9 scientists 748–757 publications: 9 scientists 758–767 publications: 3 scientists 768–777 publications: 7 scientists 778–787 publications: 7 scientists 788–797 publications: 6 scientists 798–807 publications: 2 scientists 808–817 publications: 2 scientists 818–827 publications: 7 scientists 828–837 publications: 0 scientists 838–847 publications: 9 scientists 848–857 publications: 3 scientists 858–867 publications: 1 scientists 868–877 publications: 3 scientists 878–886 publications: 6 scientists 887+ publications: 100 scientists
38 publications 887+

This scientist: 163 publications — 49th percentile

49% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 887 publications or more.

James J. DiCarlo D-index placement in Neuroscience in 2026

The chart shows the D-index (discipline H-index) distribution of Neuroscience scientists ranked by Research.com in 2026. The highlighted bar marks where James J. DiCarlo sits on this spectrum.

30–31 D-Index: 42 scientists 32–33 D-Index: 172 scientists 34–35 D-Index: 296 scientists 36–37 D-Index: 435 scientists 38–39 D-Index: 459 scientists 40–41 D-Index: 456 scientists 42–43 D-Index: 467 scientists 44–45 D-Index: 478 scientists 46–47 D-Index: 512 scientists 48–49 D-Index: 435 scientists 50–51 D-Index: 425 scientists 52–53 D-Index: 418 scientists 54–55 D-Index: 392 scientists 56–57 D-Index: 357 scientists 58–59 D-Index: 334 scientists 60–61 D-Index: 328 scientists 62–63 D-Index: 260 scientists 64–65 D-Index: 278 scientists 66–67 D-Index: 239 scientists 68–69 D-Index: 250 scientists 70–71 D-Index: 210 scientists 72–73 D-Index: 200 scientists 74–75 D-Index: 189 scientists 76–77 D-Index: 170 scientists 78–79 D-Index: 146 scientists 80–81 D-Index: 113 scientists 82–83 D-Index: 126 scientists 84–85 D-Index: 100 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 99 scientists 90–91 D-Index: 84 scientists 92–93 D-Index: 85 scientists 94–95 D-Index: 72 scientists 96–97 D-Index: 76 scientists 98–99 D-Index: 45 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 43 scientists 104–105 D-Index: 32 scientists 106–107 D-Index: 45 scientists 108–109 D-Index: 50 scientists 110–111 D-Index: 32 scientists 112–113 D-Index: 39 scientists 114–115 D-Index: 32 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 27 scientists 120–121 D-Index: 19 scientists 122–123 D-Index: 23 scientists 124–125 D-Index: 27 scientists 126–127 D-Index: 16 scientists 128–129 D-Index: 24 scientists 130–131 D-Index: 13 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 14 scientists 138–139 D-Index: 15 scientists 140–141 D-Index: 10 scientists 142–143 D-Index: 10 scientists 144–145 D-Index: 13 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 8 scientists 150–151 D-Index: 6 scientists 152–153 D-Index: 6 scientists 154–155 D-Index: 7 scientists 156–157 D-Index: 7 scientists 158–159 D-Index: 10 scientists 160–161 D-Index: 4 scientists 162 D-Index: 8 scientists 163+ D-Index: 100 scientists
30 D-Index 163+

This scientist: 68 D-Index — 72nd percentile

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

The last bar groups every scientist with 163 D-Index or more.

Research.com Recognitions

  • 2002 - Fellow of Alfred P. Sloan Foundation

Overview

James J. DiCarlo is affiliated with MIT in the United States and has a research focus primarily in neuroscience and computer science. Their work spans several subfields including cognitive neuroscience, computer vision and pattern recognition, artificial intelligence, electrical and electronic engineering, and biophysics.

The scientist's research topics include:

  • Neural dynamics and brain function
  • Face recognition and perception
  • Visual perception and processing mechanisms
  • Visual attention and saliency detection
  • Cell image analysis techniques
  • Advanced memory and neural computing
  • Memory and neural mechanisms

Notable recent publications by James J. DiCarlo are:

  • Unsupervised neural network models of the ventral visual stream, 2021, Proceedings of the National Academy of Sciences
  • Catalyzing next-generation Artificial Intelligence through NeuroAI, 2023, Nature Communications
  • Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence, 2020, Neuron
  • Fast Recurrent Processing via Ventrolateral Prefrontal Cortex Is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition, 2020, Neuron
  • Next-generation deep learning based on simulators and synthetic data, 2021, Trends in Cognitive Sciences

Frequent coauthors include:

  • Daniel Yamins
  • Kohitij Kar
  • Martin Schrimpf
  • Joel Dapello
  • Tiago Marques

The scientist has published extensively in several venues, with the most frequent being:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Journal of Vision
  • Neuron
  • Nature Communications

James J. DiCarlo was recognized as a Fellow of the Alfred P. Sloan Foundation in 2002.

Best Publications

  • How Does the Brain Solve Visual Object Recognition

    James J. DiCarlo;Davide Zoccolan;Nicole C. Rust

  • Performance-optimized hierarchical models predict neural responses in higher visual cortex

    Daniel L. K. Yamins;Ha Hong;Charles Cadieu;Ethan A. Solomon

  • Using goal-driven deep learning models to understand sensory cortex

    Daniel L K Yamins;James J DiCarlo;James J DiCarlo

  • Untangling invariant object recognition.

    James J. DiCarlo;David D. Cox

  • Fast Readout of Object Identity from Macaque Inferior Temporal Cortex

    Chou P. Hung;Chou P. Hung;Gabriel Kreiman;Tomaso Poggio;James J. DiCarlo;James J. DiCarlo

  • Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition

    Charles F. Cadieu;Ha Hong;Daniel L. K. Yamins;Nicolas Pinto

  • Why is Real-World Visual Object Recognition Hard?

    Nicolas Pinto;David Daniel Cox;David Daniel Cox;David Daniel Cox;James J DiCarlo;James J DiCarlo

  • Design of a synthetic yeast genome

    Sarah M. Richardson;Sarah M. Richardson;Leslie A. Mitchell;Leslie A. Mitchell;Giovanni Stracquadanio;Giovanni Stracquadanio;Giovanni Stracquadanio;Kun Yang;Kun Yang

  • Evidence that recurrent circuits are critical to the ventral stream's execution of core object recognition behavior.

    Kohitij Kar;Jonas Kubilius;Jonas Kubilius;Kailyn Schmidt;Elias B Issa;Elias B Issa

  • Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?

    Martin Schrimpf;Jonas Kubilius;Jonas Kubilius;Ha Hong;Najib Majaj

  • Neural population control via deep image synthesis.

    Pouya Bashivan;Kohitij Kar;James J. DiCarlo

  • Selectivity and tolerance ("invariance") both increase as visual information propagates from cortical area V4 to IT.

    Nicole C. Rust;James J. DiCarlo

  • Large-Scale, High-Resolution Comparison of the Core Visual Object Recognition Behavior of Humans, Monkeys, and State-of-the-Art Deep Artificial Neural Networks

    Rishi Rajalingham;Elias B. Issa;Pouya Bashivan;Kohitij Kar

  • Object Selectivity of Local Field Potentials and Spikes in the Macaque Inferior Temporal Cortex

    Gabriel Kreiman;Chou P. Hung;Chou P. Hung;Alexander Kraskov;Rodrigo Quian Quiroga

  • A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

    Nicolas Pinto;Nicolas Pinto;David Doukhan;David Doukhan;James J. DiCarlo;James J. DiCarlo;David Daniel Cox;David Daniel Cox;David Daniel Cox

  • Explicit information for category-orthogonal object properties increases along the ventral stream

    Ha Hong;Daniel L K Yamins;Daniel L K Yamins;Najib J Majaj;Najib J Majaj;Najib J Majaj;James J DiCarlo;James J DiCarlo

  • Unsupervised neural network models of the ventral visual stream

    Chengxu Zhuang;Siming Yan;Aran Nayebi;Martin Schrimpf

  • Stimulus configuration, classical conditioning, and hippocampal function.

    Nestor A. Schmajuk;James J. DiCarlo

  • Unsupervised Natural Experience Rapidly Alters Invariant Object Representation in Visual Cortex

    Nuo Li;James J. DiCarlo

  • Discrimination training alters object representations in human extrastriate cortex.

    Hans P. Op de Beeck;Chris I. Baker;James J. DiCarlo;Nancy G. Kanwisher

  • How far can you get with a modern face recognition test set using only simple features

    Nicolas Pinto;James J DiCarlo;David D Cox

Frequent Co-Authors

David D. Cox
David D. Cox IBM (United States)
Nancy Kanwisher
Nancy Kanwisher MIT
Kenneth O. Johnson
Kenneth O. Johnson Johns Hopkins University
Tomaso Poggio
Tomaso Poggio MIT
Gabriel Kreiman
Gabriel Kreiman Harvard University
Stanislas Dehaene
Stanislas Dehaene Collège de France
Rafael Piestun
Rafael Piestun University of Colorado Boulder
Hans Op de Beeck
Hans Op de Beeck Allen Institute for Brain Science
Wim Vanduffel
Wim Vanduffel Harvard University
Steven S. Hsiao
Steven S. Hsiao Johns Hopkins University

External Links

Wikipedia of James J. DiCarlo Personal website of James J. DiCarlo Google Scholar page

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Best Scientists Citing James J. DiCarlo

Hans Op de Beeck

Hans Op de Beeck

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Publications: 72

Tomaso Poggio

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Publications: 57

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Publications: 55

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Publications: 50

Thomas Serre

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Brown University

Publications: 41

Thomas A. Carlson

Thomas A. Carlson

University of Sydney

Publications: 37

Nancy Kanwisher

Nancy Kanwisher

MIT

Publications: 36

Nikos K. Logothetis

Nikos K. Logothetis

Chinese Academy of Sciences

Publications: 36

David D. Cox

David D. Cox

IBM (United States)

Publications: 32

Pieter R. Roelfsema

Pieter R. Roelfsema

Netherlands Institute for Neuroscience

Publications: 32

Sliman J. Bensmaia

Sliman J. Bensmaia

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Publications: 32

Itzhak Fried

Itzhak Fried

University of California, Los Angeles

Publications: 31

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Rufin Vogels

KU Leuven

Publications: 30

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Matthias Bethge

University of Tübingen

Publications: 30

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Steven S. Hsiao

Johns Hopkins University

Publications: 27

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Publications: 25

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