World's Best Scientists 2026 revealed!
Richard G. Baraniuk

Richard G. Baraniuk

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Computer Science
USA
2026
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Electronics and Electrical Engineering
USA
2026

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
113
Citations
67991
World Ranking
87
National Ranking
42

Computer Science

D-Index
120
Citations
76110
World Ranking
144
National Ranking
84

Richard G. Baraniuk publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Richard G. Baraniuk sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 548 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Richard G. Baraniuk D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Richard G. Baraniuk sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 113 D-Index — 99th percentile

99% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2026 - Research.com Computer Science in United States Leader Award
  • 2026 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2025 - Research.com Computer Science in United States Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2023 - Research.com Computer Science in United States Leader Award
  • 2022 - Research.com Computer Science in United States Leader Award
  • 2017 - Fellow of the American Academy of Arts and Sciences
  • 2016 - Fellow, National Academy of Inventors
  • 2009 - Fellow of the American Association for the Advancement of Science (AAAS)

Overview

Richard G. Baraniuk is affiliated with Rice University in the United States. Their research predominantly spans the field of Computer Science, with a strong focus on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Mechanics, Biomedical Engineering, and Statistics and Probability.

The scientist's work addresses a variety of topics within these areas, including:

  • Topic Modeling
  • Generative Adversarial Networks and Image Synthesis
  • Domain Adaptation and Few-Shot Learning
  • Natural Language Processing Techniques
  • Anomaly Detection Techniques and Applications
  • Intelligent Tutoring Systems and Adaptive Learning
  • Advanced Neural Network Applications

Baraniuk's publication record includes recent papers such as:

  • "Deep Learning Techniques for Inverse Problems in Imaging" (2020, IEEE Journal on Selected Areas in Information Theory)
  • "Current progress and open challenges for applying deep learning across the biosciences" (2022, Nature Communications)
  • "Clustering earthquake signals and background noises in continuous seismic data with unsupervised deep learning" (2020, Nature Communications)
  • "Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference" (2020, IEEE Journal of Selected Topics in Signal Processing)
  • "The science of deep learning" (2020, Proceedings of the National Academy of Sciences)

Their frequent co-authors include:

  • Randall Balestriero
  • Shashank Sonkar
  • Naiming Liu
  • Ahmed Imtiaz Humayun
  • Zichao Wang

The venues where Baraniuk has published regularly include:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • SIAM Journal on Mathematics of Data Science
  • IEEE Transactions on Signal Processing
  • IEEE Journal on Selected Areas in Information Theory

Richard G. Baraniuk has received recognition from several organizations, including:

  • Fellow of the American Academy of Arts and Sciences (2017)
  • Fellow, National Academy of Inventors (2016)
  • Fellow of the American Association for the Advancement of Science (AAAS) (2009)

Best Publications

  • Compressive Sensing [Lecture Notes]

    R.G. Baraniuk

  • Single-Pixel Imaging via Compressive Sampling

    M.F. Duarte;M.A. Davenport;D. Takhar;J.N. Laska

  • The dual-tree complex wavelet transform

    I.W. Selesnick;R.G. Baraniuk;N.C. Kingsbury

  • A Simple Proof of the Restricted Isometry Property for Random Matrices

    Richard G. Baraniuk;Mark A. Davenport;Ronald A. DeVore;Michael B. Wakin

  • Wavelet-based statistical signal processing using hidden Markov models

    M.S. Crouse;R.D. Nowak;R.G. Baraniuk

  • Model-Based Compressive Sensing

    R.G. Baraniuk;V. Cevher;M.F. Duarte;C. Hegde

  • Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

    J.A. Tropp;J.N. Laska;M.F. Duarte;J.K. Romberg

  • Compressive Radar Imaging

    R. Baraniuk;P. Steeghs

  • pathChirp: Efficient available bandwidth estimation for network paths

    Vinay J. Ribeiro;Jiri Navratil;Rudolf H. Riedi;Richard G. Baraniuk

  • Material parameter estimation with terahertz time-domain spectroscopy

    Timothy D. Dorney;Richard G. Baraniuk;Daniel M. Mittleman

  • Recent advances in terahertz imaging

    D.M. Mittleman;M. Gupta;R. Neelamani;R.G. Baraniuk

  • A single-pixel terahertz imaging system based on compressed sensing

    Wai Lam Chan;Kriti Charan;Dharmpal Takhar;Kevin F. Kelly

  • A multifractal wavelet model with application to network traffic

    R.H. Riedi;M.S. Crouse;V.J. Ribeiro;R.G. Baraniuk

  • Fast Alternating Direction Optimization Methods

    Tom Goldstein;Brendan O'Donoghue;Simon Setzer;Richard G. Baraniuk

  • 1-Bit compressive sensing

    P.T. Boufounos;R.G. Baraniuk

  • A new compressive imaging camera architecture using optical-domain compression

    Dharmpal Takhar;Jason N. Laska;Michael B. Wakin;Marco F. Duarte

  • Bayesian tree-structured image modeling using wavelet-domain hidden Markov models

    J.K. Romberg;Hyeokho Choi;R.G. Baraniuk

  • Signal Processing With Compressive Measurements

    M.A. Davenport;P.T. Boufounos;M.B. Wakin;R.G. Baraniuk

  • Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors

    L. Jacques;J. N. Laska;P. T. Boufounos;R. G. Baraniuk

  • From Denoising to Compressed Sensing

    Christopher A. Metzler;Arian Maleki;Richard G. Baraniuk

  • Compressive sensing

    R. Baraniuk

Frequent Co-Authors

Michael B. Wakin
Michael B. Wakin Colorado School of Mines
Marco F. Duarte
Marco F. Duarte University of Massachusetts Amherst
Mark A. Davenport
Mark A. Davenport Georgia Institute of Technology
Aswin C. Sankaranarayanan
Aswin C. Sankaranarayanan Carnegie Mellon University
Rudolf H. Riedi
Rudolf H. Riedi Rice University
Robert Nowak
Robert Nowak University of Wisconsin–Madison
Douglas L. Jones
Douglas L. Jones University of Illinois at Urbana-Champaign
Ashok Veeraraghavan
Ashok Veeraraghavan Rice University
Petros T. Boufounos
Petros T. Boufounos Mitsubishi Electric (United States)

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