World's Best Scientists 2026 revealed!

D-Index & Metrics

Neuroscience

D-Index
79
Citations
25530
World Ranking
1669
National Ranking
817

Engineering and Technology

D-Index
74
Citations
24431
World Ranking
797
National Ranking
277

Konrad P. Kording 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 Konrad P. Kording 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: 296 publications — 75th percentile

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

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

Konrad P. Kording 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 Konrad P. Kording 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: 74 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Overview

Konrad P. Kording is affiliated with the University of Pennsylvania in the United States. Their research primarily spans the field of Neuroscience, with a total of 80 publications in this domain. Within Neuroscience, their subfields of focus include Cognitive Neuroscience, Artificial Intelligence, Molecular Biology, Electrical and Electronic Engineering, and Experimental and Cognitive Psychology.

The scientist's work covers various specialized topics, including:

  • Neural dynamics and brain function
  • Functional Brain Connectivity Studies
  • Advanced Memory and Neural Computing
  • Neural Networks and Applications
  • EEG and Brain-Computer Interfaces
  • Domain Adaptation and Few-Shot Learning
  • Visual perception and processing mechanisms

Kording has contributed to several recent papers, which include:

  • "Tackling Climate Change with Machine Learning," 2022, OPUS 4 (Zuse Institute Berlin)
  • "Causal mapping of human brain function," 2022, Nature Reviews. Neuroscience
  • "Different scaling of linear models and deep learning in UKBiobank brain images versus machine-learning datasets," 2020, Nature Communications
  • "Catalyzing next-generation Artificial Intelligence through NeuroAI," 2023, Nature Communications
  • "The neuroconnectionist research programme," 2023, Nature Reviews. Neuroscience

Their frequent co-authors are Jordan Matelsky, Ari S. Benjamin, Titipat Achakulvisut, Lyle Ungar, and Eva L. Dyer, with collaboration counts ranging from 8 to 11 joint publications each.

Publications are often found in several notable venues. Kording has published extensively in arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), Trends in Cognitive Sciences, Nature Communications, and PLoS ONE.

Best Publications

  • Bayesian integration in sensorimotor learning

    Konrad P. Körding;Daniel M. Wolpert

  • Causal inference in multisensory perception.

    Konrad P. Körding;Ulrik Beierholm;Wei Ji Ma;Steven Quartz

  • Bayesian decision theory in sensorimotor control.

    Konrad P. Körding;Daniel M. Wolpert

  • A deep learning framework for neuroscience

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

  • Toward an Integration of Deep Learning and Neuroscience.

    Adam H. Marblestone;Greg Wayne;Konrad P. Kording

  • Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study

    Sohrab Saeb;Mi Zhang;Christopher J Karr;Stephen M Schueller

  • How advances in neural recording affect data analysis

    Ian H Stevenson;Konrad P Kording;Konrad P Kording

  • Over my fake body: body ownership illusions for studying the multisensory basis of own-body perception

    Konstantina Kilteni;Antonella Maselli;Konrad P. Kording;Konrad P. Kording;Mel Slater

  • The dynamics of memory as a consequence of optimal adaptation to a changing body

    Konrad Paul Kording;Joshua B. Tenenbaum;Reza Shadmehr

  • Relevance of Error : What Drives Motor Adaptation?

    Kunlin Wei;Konrad P. Kording

  • Decision Theory: What "Should" the Nervous System Do?

    Konrad Körding

  • Estimating the sources of motor errors for adaptation and generalization.

    Max Berniker;Konrad Kording

  • Could a Neuroscientist Understand a Microprocessor

    Eric Jonas;Konrad Paul Kording

  • The statistics of natural hand movements

    James N. Ingram;Konrad P. Körding;Ian S. Howard;Daniel M. Wolpert

  • Physical principles for scalable neural recording

    Adam Henry Marblestone;Bradley M Zamft;Yael G Maguire;Mikhail G Shapiro

  • The relationship between mobile phone location sensor data and depressive symptom severity.

    Sohrab Saeb;Emily G. Lattie;Stephen M. Schueller;Konrad P. Kording

  • Towards an integration of deep learning and neuroscience

    Adam Marblestone;Greg Wayne;Konrad Kording

  • Catalyzing next-generation Artificial Intelligence through NeuroAI

    Unknown

  • Multisensory perception: from integration to remapping

    Julia Trommershäuser;Konrad P. Körding;Michael S. Landy

  • Bayesian models: the structure of the world, uncertainty, behavior, and the brain

    Iris Vilares;Iris Vilares;Konrad Kording

  • Tackling Climate Change with Machine Learning

    David Rolnick;Priya L. Donti;Lynn H. Kaack;Kelly Kochanski

Frequent Co-Authors

Lee E. Miller
Lee E. Miller Northwestern University
George M. Church
George M. Church Harvard University
Peter König
Peter König Osnabrück University
David C. Mohr
David C. Mohr Northwestern University
Christoph Kayser
Christoph Kayser Bielefeld University
Daniel M. Wolpert
Daniel M. Wolpert Columbia University
Eric J. Perreault
Eric J. Perreault Northwestern University
Paul Schrater
Paul Schrater University of Minnesota
Levi J. Hargrove
Levi J. Hargrove Northwestern University

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