2026 John P. Cunningham: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	45	7024	6820	3079	2963	135	14150

Research.com Recognitions

2015 - Fellow of Alfred P. Sloan Foundation

Overview

John P. Cunningham is affiliated with Columbia University in the United States. Their research spans multiple fields, primarily in Computer Science and Neuroscience, with a considerable focus on subfields such as Artificial Intelligence, Cognitive Neuroscience, Computer Vision and Pattern Recognition, Statistics and Probability, and Molecular Biology.

The scientist's work covers a variety of topics, including:

Neural dynamics and brain function
Gaussian Processes and Bayesian Inference
Functional Brain Connectivity Studies
EEG and Brain-Computer Interfaces
Machine Learning and Data Classification
Artificial Intelligence in Healthcare and Education
Motor Control and Adaptation

John P. Cunningham has contributed to several well-known publication venues, often publishing most frequently in:

arXiv (Cornell University)
bioRxiv (Cold Spring Harbor Laboratory)
eLife
Neuron
Nature Communications

Notable recent papers include:

"Almanac - Retrieval-Augmented Language Models for Clinical Medicine" (2024, NEJM AI)
"Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation" (2020, Neuron)
"Flexible neural control of motor units" (2022, Nature Neuroscience)
"Motor cortex activity across movement speeds is predicted by network-level strategies for generating muscle activity" (2022, eLife)
"Predicting post-operative right ventricular failure using video-based deep learning" (2021, Nature Communications)

The scientist frequently collaborates with peers such as Geoff Pleiss, Liam Paninski, Mark M. Churchland, David M. Blei, and E. Kelly Buchanan.

In terms of recognition, John P. Cunningham was awarded the Alfred P. Sloan Foundation Fellowship in 2015.

Best Publications

Neural population dynamics during reaching

Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Justin D. Foster

1874
Citations
Dimensionality reduction for large-scale neural recordings.

John P Cunningham;Byron M Yu

1308
Citations
Stimulus onset quenches neural variability: a widespread cortical phenomenon

Mark M. Churchland;Byron M. Yu;Byron M. Yu;John P. Cunningham;Leo P. Sugrue;Leo P. Sugrue

1286
Citations
Influence of heart rate on the BOLD signal: the cardiac response function

Catie Chang;John P. Cunningham;Gary H. Glover

814
Citations
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity

Byron M Yu;John P Cunningham;Gopal Santhanam;Stephen I. Ryu

813
Citations
A high-performance neural prosthesis enabled by control algorithm design

Vikash Gilja;Paul Nuyujukian;Cindy A Chestek;John P Cunningham;John P Cunningham

638
Citations
Cortical Preparatory Activity: Representation of Movement or First Cog in a Dynamical Machine?

Mark M. Churchland;John P. Cunningham;John P. Cunningham;Matthew T. Kaufman;Stephen I. Ryu;Stephen I. Ryu

590
Citations
Linear dimensionality reduction: survey, insights, and generalizations

John P. Cunningham;Zoubin Ghahramani

533
Citations
Reorganization between preparatory and movement population responses in motor cortex

Gamaleldin F. Elsayed;Antonio H. Lara;Matthew T. Kaufman;Mark M. Churchland

476
Citations
Long-term stability of neural prosthetic control signals from silicon cortical arrays in rhesus macaque motor cortex

Cynthia A Chestek;Vikash Gilja;Paul Nuyujukian;Justin D Foster

411
Citations
Bayesian Optimization with Inequality Constraints

Jacob Gardner;Matt Kusner;Zhixiang;Kilian Weinberger

401
Citations
Towards the neural population doctrine.

Shreya Saxena;John P Cunningham

329
Citations
Motor Cortex Embeds Muscle-like Commands in an Untangled Population Response

Abigail A. Russo;Abigail A. Russo;Sean R. Bittner;Sean R. Bittner;Sean M. Perkins;Jeffrey S. Seely;Jeffrey S. Seely

321
Citations
Empirical models of spiking in neural populations

Jakob H Macke;Lars Buesing;John P Cunningham;Byron M Yu

234
Citations
Single-trial dynamics of motor cortex and their applications to brain-machine interfaces

Jonathan C. Kao;Paul Nuyujukian;Stephen I. Ryu;Mark M. Churchland

211
Citations
A closed-loop human simulator for investigating the role of feedback control in brain-machine interfaces

John Patrick Cunningham;John Patrick Cunningham;Paul Nuyujukian;Vikash Gilja;Cindy A Chestek

199
Citations
BLACK BOX VARIATIONAL INFERENCE FOR STATE SPACE MODELS

Evan Archer;Il Memming Park;Lars Buesing;John Cunningham

174
Citations
Structure in neural population recordings: an expected byproduct of simpler phenomena?

Gamaleldin F Elsayed;John P Cunningham

173
Citations
Neural Trajectories in the Supplementary Motor Area and Motor Cortex Exhibit Distinct Geometries, Compatible with Different Classes of Computation.

Abigail A. Russo;Ramin Khajeh;Sean R. Bittner;Sean M. Perkins

169
Citations
Fast Kernel Learning for Multidimensional Pattern Extrapolation

Andrew Wilson;Elad Gilboa;John P Cunningham;Arye Nehorai

156
Citations
Linear dynamical neural population models through nonlinear embeddings

Yuanjun Gao;Evan W. Archer;Liam Paninski;John P. Cunningham

138
Citations

Frequent Co-Authors

Liam Paninski Columbia University

Krishna V. Shenoy Stanford University

Stephen I. Ryu Stanford University

Mark M. Churchland Columbia University

Byron M. Yu Carnegie Mellon University

Maneesh Sahani University College London

Anne K. Churchland University of California, Los Angeles

William T. Newsome Stanford University

Zoubin Ghahramani University of Cambridge

Arye Nehorai Washington University in St. Louis

External Links

Personal website of John P. Cunningham Google Scholar page

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