World's Best Scientists 2026 revealed!
Nikolaus Kriegeskorte

Nikolaus Kriegeskorte

D-Index & Metrics

Neuroscience

D-Index
74
Citations
33312
World Ranking
2063
National Ranking
982

Engineering and Technology

D-Index
66
Citations
30866
World Ranking
1367
National Ranking
448

Nikolaus Kriegeskorte 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 Nikolaus Kriegeskorte 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: 214 publications — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Nikolaus Kriegeskorte 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 Nikolaus Kriegeskorte 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: 66 D-Index — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Overview

Nikolaus Kriegeskorte is affiliated with Columbia University in the United States. Their research spans the fields of neuroscience and computer science, with a particular focus on cognitive neuroscience, computer vision and pattern recognition, and artificial intelligence. They have contributed extensively to topics such as neural dynamics and brain function, face recognition and perception, functional brain connectivity studies, visual perception and processing mechanisms, visual attention and saliency detection, child and animal learning development, and action observation and synchronization.

Their notable recent publications include:

  • The neuroconnectionist research programme, 2023, published in Nature Reviews. Neuroscience
  • Neural tuning and representational geometry, 2021, published in Nature Reviews. Neuroscience
  • Individual differences among deep neural network models, 2020, published in Nature Communications
  • An ecologically motivated image dataset for deep learning yields better models of human vision, 2021, published in Proceedings of the National Academy of Sciences
  • Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision, 2020, published in PLoS Computational Biology

Nikolaus Kriegeskorte frequently collaborates with co-authors including Tal Golan, Benjamin Peters, Tim C. Kietzmann, Katherine R. Storrs, and Heiko H. Schütt. These collaborations are reflected in numerous publications across their research domains.

Their work has been published extensively in venues such as:

  • Journal of Vision
  • bioRxiv (Cold Spring Harbor Laboratory)
  • arXiv (Cornell University)
  • Proceedings of the National Academy of Sciences
  • Zenodo (CERN European Organization for Nuclear Research)

The research by Nikolaus Kriegeskorte addresses complex mechanisms underlying brain function and perception, employing computational models and empirical data to explore how neural systems support cognitive processes. Their interdisciplinary approach integrates methods from neuroscience, machine learning, and psychology to investigate visual recognition, neural coding, and learning development.

Best Publications

  • Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

    Nikolaus Kriegeskorte;Marieke Mur;Peter A Bandettini

  • Circular analysis in systems neuroscience: the dangers of double dipping.

    Nikolaus Kriegeskorte;W Kyle Simmons;Patrick S F Bellgowan;Chris I Baker

  • Information-based functional brain mapping

    Nikolaus Kriegeskorte;Rainer Goebel;Peter Bandettini

  • Matching Categorical Object Representations in Inferior Temporal Cortex of Man and Monkey

    Nikolaus Kriegeskorte;Marieke Mur;Marieke Mur;Douglas A. Ruff;Roozbeh Kiani

  • Deep supervised, but not unsupervised, models may explain IT cortical representation.

    Seyed Mahdi Khaligh-Razavi;Nikolaus Kriegeskorte

  • Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing

    Nikolaus Kriegeskorte

  • Representational geometry: integrating cognition, computation, and the brain

    Nikolaus Kriegeskorte;Rogier A. Kievit;Rogier A. Kievit

  • A deep learning framework for neuroscience

    Blake A Richards;Timothy P Lillicrap;Philippe Beaudoin;Yoshua Bengio;Yoshua Bengio

  • A toolbox for representational similarity analysis.

    Hamed Nili;Cai Arran Wingfield;Alexander Walther;Li Su

  • Best practices in data analysis and sharing in neuroimaging using MRI.

    Thomas E Nichols;Samir Das;Samir Das;Simon B Eickhoff;Simon B Eickhoff;Alan C Evans;Alan C Evans

  • Reliability of dissimilarity measures for multi-voxel pattern analysis.

    Alexander Walther;Alexander Walther;Hamed Nili;Naveed Ejaz;Arjen Alink

  • Individual faces elicit distinct response patterns in human anterior temporal cortex

    Nikolaus Kriegeskorte;Elia Formisano;Bettina Sorger;Rainer Goebel

  • Comparison of multivariate classifiers and response normalizations for pattern-information fMRI.

    Masaya Misaki;Youn Kim;Youn Kim;Peter A. Bandettini;Nikolaus Kriegeskorte;Nikolaus Kriegeskorte

  • Cognitive computational neuroscience

    Nikolaus Kriegeskorte;Pamela K. Douglas

  • Neural network models and deep learning.

    Nikolaus Kriegeskorte;Tal Golan

  • Neural correlates of trust

    Frank Krueger;Kevin McCabe;Jorge Moll;Nikolaus Kriegeskorte

  • Revealing representational content with pattern-information fMRI—an introductory guide

    Marieke Mur;Peter A. Bandettini;Nikolaus Kriegeskorte

  • Representational dynamics of object vision: The first 1000 ms

    Thomas Carlson;Thomas Carlson;David A. Tovar;Arjen Alink;Nikolaus Kriegeskorte

  • Cortical capacity constraints for visual working memory: dissociation of fMRI load effects in a fronto-parietal network.

    David Edmund Johannes Linden;Robert A. Bittner;Lars Muckli;James A. Waltz

  • Recurrence is required to capture the representational dynamics of the human visual system

    Tim C. Kietzmann;Tim C. Kietzmann;Courtney J. Spoerer;Lynn K. A. Sörensen;Radoslaw M. Cichy

  • Deep neural networks: a new framework for modelling biological vision and brain information processing

    Nikolaus Kriegeskorte

Frequent Co-Authors

Peter A. Bandettini
Peter A. Bandettini National Institutes of Health
James B. Rowe
James B. Rowe University of Cambridge
Thomas A. Carlson
Thomas A. Carlson University of Sydney
Kendrick Kay
Kendrick Kay University of Minnesota
Rainer Goebel
Rainer Goebel Maastricht University
Jörn Diedrichsen
Jörn Diedrichsen University of Western Ontario
Pascal Belin
Pascal Belin Aix-Marseille University
Wolf Singer
Wolf Singer Ernst Strüngmann Institute for Neuroscience
Olaf Hauk
Olaf Hauk MRC Cognition and Brain Sciences Unit

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Studying Engineering and Technology in the USA opens diverse career options beyond traditional roles. Many students now explore specialized online degrees to broaden their expertise and increase employability. Popular options like the cheapest online master's in project management offer leadership skills for managing technical teams and complex projects, all while being budget-friendly.

Students interested in the intersection of technology and design can consider earning an online ux design degree. This credential prepares graduates for high-demand roles in creating user-friendly digital products. Alternatively, those aiming for careers in property management, development, or brokerage might explore a cheap online real estate school for flexible and affordable learning options.

Wondering where a project management qualification could lead? Learn more about what can i do with a project management degree to get insights into job opportunities and industry growth. By choosing the right online program, students can align their education with evolving industry needs and carve out rewarding career pathways.

Best Scientists Citing Nikolaus Kriegeskorte

Trending Scientists

Recently Published Articles