World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
23408
World Ranking
2159
National Ranking
1085

Liam Paninski 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 Liam Paninski 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: 252 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Liam Paninski 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 Liam Paninski 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: 67 D-Index — 85th percentile

85% 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

  • 2007 - Fellow of Alfred P. Sloan Foundation

Overview

Liam Paninski is affiliated with Columbia University in the United States and conducts research primarily in the fields of Neuroscience and Biochemistry, Genetics and Molecular Biology.

Their recent publications include:

  • NeuroPAL: A Multicolor Atlas for Whole-Brain Neuronal Identification in C. elegans, 2020, Cell
  • Reconstruction of neocortex: Organelles, compartments, cells, circuits, and activity, 2022, Cell
  • Rapid mesoscale volumetric imaging of neural activity with synaptic resolution, 2020, Nature Methods
  • Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data, 2020, PLoS Computational Biology
  • YASS: Yet Another Spike Sorter applied to large-scale multi-electrode array recordings in primate retina, 2020, bioRxiv (Cold Spring Harbor Laboratory)

The scientist frequently publishes in the following venues:

  • bioRxiv (Cold Spring Harbor Laboratory)
  • PLoS Computational Biology
  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Nature Methods

Liam Paninski's research spans several subfields of study, including:

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience
  • Biophysics
  • Aging
  • Electrical and Electronic Engineering

Their main research topics include:

  • Neural dynamics and brain function
  • Cell Image Analysis Techniques
  • Genetics, Aging, and Longevity in Model Organisms
  • Photoreceptor and optogenetics research
  • Advanced Fluorescence Microscopy Techniques
  • Advanced Memory and Neural Computing
  • Neuroscience and Neural Engineering

Liam Paninski has collaborated extensively with several frequent co-authors, such as:

  • Erdem Varol
  • Amin Nejatbakhsh
  • Eviatar Yemini
  • Oliver Hobert
  • Matthew R Whiteway

Among awards, Liam Paninski was recognized as a Fellow of the Alfred P. Sloan Foundation in 2007.

Best Publications

  • Instant neural control of a movement signal.

    Mijail D. Serruya;Nicholas G. Hatsopoulos;Nicholas G. Hatsopoulos;Liam Paninski;Liam Paninski;Matthew R. Fellows

  • Estimation of entropy and mutual information

    Liam Paninski

  • Spatio-temporal correlations and visual signalling in a complete neuronal population

    Jonathan William Pillow;Jonathon Shlens;Liam Paninski;Alexander Sher

  • Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition

    Wulfram Gerstner;Werner M. Kistler;Richard Naud;Liam Paninski

  • Simultaneous Denoising, Deconvolution, and Demixing of Calcium Imaging Data

    Eftychios A. Pnevmatikakis;Daniel Soudry;Yuanjun Gao;Timothy A. Machado

  • Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

    Pengcheng Zhou;Shanna L Resendez;Jose Rodriguez-Romaguera;Jessica C Jimenez

  • Maximum likelihood estimation of cascade point-process neural encoding models

    Liam Paninski

  • Fast online deconvolution of calcium imaging data.

    Johannes Friedrich;Pengcheng Zhou;Pengcheng Zhou;Liam Paninski

  • Fast Nonnegative Deconvolution for Spike Train Inference From Population Calcium Imaging

    Joshua T. Vogelstein;Adam M. Packer;Timothy A. Machado;Tanya Sippy

  • Spatiotemporal Tuning of Motor Cortical Neurons for Hand Position and Velocity

    Liam Paninski;Matthew R. Fellows;Nicholas G. Hatsopoulos;John P. Donoghue

  • Prediction and decoding of retinal ganglion cell responses with a probabilistic spiking model.

    Jonathan W. Pillow;Liam Paninski;Valerie J. Uzzell;Eero P. Simoncelli

  • Functional connectivity in the retina at the resolution of photoreceptors

    Greg D. Field;Jeffrey L. Gauthier;Jeffrey L. Gauthier;Alexander Sher;Martin Greschner

  • Fast non-negative deconvolution for spike train inference from population calcium imaging

    Joshua T. Vogelstein;Adam M. Packer;Tim A. Machado;Tanya Sippy

  • Characterization of Neural Responses with Stochastic Stimuli

    Eero Simoncelli;Jonathan W. Pillow;Jonathan W. Pillow;Jonathan W. Pillow;Liam Paninski;Liam Paninski;Liam Paninski;Odelia Schwartz;Odelia Schwartz;Odelia Schwartz

  • Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Encoding Model

    Liam Paninski;Jonathan W. Pillow;Eero P. Simoncelli

  • Statistical models for neural encoding, decoding, and optimal stimulus design

    Liam Paninski;Jonathan William Pillow;Jeremy Lewi

  • Information about movement direction obtained from synchronous activity of motor cortical neurons

    Nicholas G. Hatsopoulos;Catherine L. Ojakangas;Liam Paninski;John P. Donoghue

  • Spike Inference from Calcium Imaging Using Sequential Monte Carlo Methods

    Joshua T. Vogelstein;Brendon O. Watson;Adam M. Packer;Rafael Yuste;Rafael Yuste

  • A new look at state-space models for neural data

    Liam Paninski;Yashar Ahmadian;Daniel Gil Ferreira;Shinsuke Koyama

  • A Coincidence-Based Test for Uniformity Given Very Sparsely Sampled Discrete Data

    L. Paninski

  • Fast Active Set Methods for Online Deconvolution of Calcium Imaging Data

    Johannes Friedrich;Pengcheng Zhou;Liam Paninski

Frequent Co-Authors

John P. Cunningham
John P. Cunningham Columbia University
Wulfram Gerstner
Wulfram Gerstner École Polytechnique Fédérale de Lausanne
E. J. Chichilnisky
E. J. Chichilnisky Stanford University
Jonathan W. Pillow
Jonathan W. Pillow Princeton University
Eero P. Simoncelli
Eero P. Simoncelli New York University
Rafael Yuste
Rafael Yuste Columbia University
Nicholas G. Hatsopoulos
Nicholas G. Hatsopoulos University of Chicago
Misha B. Ahrens
Misha B. Ahrens Howard Hughes Medical Institute
Hillel Adesnik
Hillel Adesnik University of California, Berkeley
Anne K. Churchland
Anne K. Churchland University of California, Los Angeles

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