World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
13883
World Ranking
5677
National Ranking
1582

Research.com Recognitions

  • 2013 - IEEE Fellow For contributions to sparse signal recovery algorithms and dictionary learning

Overview

Kenneth Kreutz-Delgado is affiliated with the University of California, San Diego in the United States. Their research spans across multiple domains within computer science and neuroscience, with a focus on neural dynamics, brain function, and advanced computational techniques.

The scientist has contributed to several prominent fields of study, including:

  • Computer Science
  • Neuroscience

Within these fields, their work delves into subfields such as:

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Computational Mechanics

The main topics covered by their publications include:

  • Neural dynamics and brain function
  • EEG and Brain-Computer Interfaces
  • Functional Brain Connectivity Studies
  • Neural Networks and Applications
  • Blind Source Separation Techniques
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Neural Network Applications

Kenneth Kreutz-Delgado has authored a number of papers in respected venues. Selected recent publications are:

  • The open EEGLAB portal Interface: High-Performance computing with EEGLAB, 2020, NeuroImage
  • Bridging M/EEG Source Imaging and Independent Component Analysis Frameworks Using Biologically Inspired Sparsity Priors, 2021, Neural Computation
  • What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?, 2020, Entropy
  • A Competitive Edge: Can FPGAs Beat GPUs at DCNN Inference Acceleration in Resource-Limited Edge Computing Applications?, 2021, arXiv (Cornell University)
  • Training Deep Neural Networks with Joint Quantization and Pruning of Weights and Activations, 2021, arXiv (Cornell University)

Their frequent co-authors include:

  • Srinjoy Das
  • Ramón Martínez-Cancino
  • Arnaud Delorme
  • Scott Makeig
  • Ian Colbert

Kenneth Kreutz-Delgado has frequently published in these venues:

  • arXiv (Cornell University)
  • NeuroImage
  • Neural Computation
  • Entropy
  • Preprints.org

Among their recognitions, Kenneth Kreutz-Delgado is an IEEE Fellow since 2013, awarded for contributions to sparse signal recovery algorithms and dictionary learning.

Best Publications

  • ICLabel: An automated electroencephalographic independent component classifier, dataset, and website.

    Luca Pion-Tonachini;Kenneth Kreutz-Delgado;Scott Makeig

  • Sparse solutions to linear inverse problems with multiple measurement vectors

    S.F. Cotter;B.D. Rao;Kjersti Engan;K. Kreutz-Delgado

  • The attitude control problem

    J.T.-Y. Wen;K. Kreutz-Delgado

  • Dictionary learning algorithms for sparse representation

    Kenneth Kreutz-Delgado;Joseph F. Murray;Bhaskar D. Rao;Kjersti Engan

  • An affine scaling methodology for best basis selection

    B.D. Rao;K. Kreutz-Delgado

  • The Complex Gradient Operator and the CR-Calculus

    Ken Kreutz-Delgado

  • Subset selection in noise based on diversity measure minimization

    B.D. Rao;K. Engan;S.F. Cotter;J. Palmer

  • Machine Learning Methods for Predicting Failures in Hard Drives: A Multiple-Instance Application

    Joseph F. Murray;Gordon F. Hughes;Kenneth Kreutz-Delgado

  • A spatial operator algebra for manipulator modeling and control

    G. Rodriguez;K. Kreutz-Delgado;A. Jain

  • A grid algorithm for autonomous star identification

    C. Padgett;K. Kreutz-Delgado

  • Improved disk-drive failure warnings

    G.F. Hughes;J.F. Murray;K. Kreutz-Delgado;C. Elkan

  • Newton method for the ICA mixture model

    J.A. Palmer;S. Makeig;K.K. Delgado;B.D. Rao

  • Event-driven contrastive divergence for spiking neuromorphic systems

    Emre Neftci;Srinjoy Das;Bruno U. Pedroni;Kenneth Kreutz-Delgado

  • Variational EM Algorithms for Non-Gaussian Latent Variable Models

    Jason Palmer;Kenneth Kreutz-Delgado;Bhaskar D. Rao;David P. Wipf

  • Evolving Signal Processing for Brain–Computer Interfaces

    S. Makeig;C. Kothe;T. Mullen;N. Bigdely-Shamlo

  • Motion and force control of multiple robotic manipulators

    John T. Wen;Kenneth Kreutz-Delgado

  • Kinematic analysis of 7-DOF manipulators

    Kenneth Kreutz-Delgado;Mark Long;Homayoun Seraji

  • Spatial Operator Algebra for multibody system dynamics

    G. Rodriguez;A. Jain;K. Kreutz-Delgado

  • Evaluation of Star Identification Techniques

    Curtis Padgett;Kenneth Kreutz-Delgado;Suraphol Udomkesmalee

  • Super-Gaussian mixture source model for ICA

    Jason A. Palmer;Kenneth Kreutz-Delgado;Scott Makeig

Frequent Co-Authors

Scott Makeig
Scott Makeig University of California, San Diego
Bhaskar D. Rao
Bhaskar D. Rao University of California, San Diego
Gert Cauwenberghs
Gert Cauwenberghs University of California, San Diego
Terrence J. Sejnowski
Terrence J. Sejnowski Salk Institute for Biological Studies
Arnaud Delorme
Arnaud Delorme University of California, San Diego
Dharmendra S. Modha
Dharmendra S. Modha IBM (United States)
David Wipf
David Wipf Amazon (United States)
Martin I. Sereno
Martin I. Sereno San Diego State University
Homayoun Seraji
Homayoun Seraji California Institute of Technology
John T. Wen
John T. Wen Rensselaer Polytechnic Institute

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