World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
23408
World Ranking
2159
National Ranking
1084

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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