World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
11828
World Ranking
5811
National Ranking
2642

Jonathan Le Roux 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 Jonathan Le Roux 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: 137 publications — 21st percentile

21% of scientists in this discipline score the same or lower.

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

Jonathan Le Roux 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 Jonathan Le Roux 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: 49 D-Index — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Jonathan Le Roux is affiliated with Mitsubishi Electric (United States) and has contributed extensively to research in computer science, specifically focusing on signal processing and artificial intelligence. Their work spans a range of subfields including signal processing, artificial intelligence, computer vision and pattern recognition, computational mechanics, and cognitive neuroscience.

The main topics addressed in Jonathan Le Roux's research include:

  • Speech and Audio Processing
  • Music and Audio Processing
  • Speech Recognition and Synthesis
  • Advanced Adaptive Filtering Techniques
  • Multimodal Machine Learning Applications
  • Human Pose and Action Recognition
  • Hearing Loss and Rehabilitation

Le Roux's recent publications illustrate their focus on audio and speech-related technologies. Notable papers include:

  • "STFT-Domain Neural Speech Enhancement With Very Low Algorithmic Latency," 2022, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "(2.5+1)D Spatio-Temporal Scene Graphs for Video Question Answering," 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "The Cocktail Fork Problem: Three-Stem Audio Separation for Real-World Soundtracks," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "Convolutive Prediction for Monaural Speech Dereverberation and Noisy-Reverberant Speaker Separation," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing

Frequently collaborating with other researchers, Le Roux's notable coauthors include:

  • Gordon Wichern
  • Zhong-Qiu Wang
  • Takaaki Hori
  • Chiori Hori
  • Darius Petermann

The scientist's work has appeared repeatedly in several prominent venues, reflecting a consistent engagement with leading conferences and journals in their domains. These venues include:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence

Best Publications

  • Deep clustering: Discriminative embeddings for segmentation and separation

    John R. Hershey;Zhuo Chen;Jonathan Le Roux;Shinji Watanabe

  • SDR – Half-baked or Well Done?

    Jonathan Le Roux;Scott Wisdom;Hakan Erdogan;John R. Hershey

  • Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

    Hakan Erdogan;John R. Hershey;Shinji Watanabe;Jonathan Le Roux

  • Speech Enhancement with LSTM Recurrent Neural Networks and its Application to Noise-Robust ASR

    Felix Weninger;Hakan Erdogan;Shinji Watanabe;Emmanuel Vincent

  • Deep Unfolding: Model-Based Inspiration of Novel Deep Architectures

    John R. Hershey;Jonathan Le Roux;Felix Weninger

  • Single-Channel Multi-Speaker Separation using Deep Clustering

    Yusuf Ziya Isik;Yusuf Ziya Isik;Jonathan Le Roux;Zhuo Chen;Zhuo Chen;Shinji Watanabe

  • Improved MVDR beamforming using single-channel mask prediction networks

    Hakan Erdogan;John R. Hershey;Shinji Watanabe;Michael I. Mandel

  • The second ‘chime’ speech separation and recognition challenge: Datasets, tasks and baselines

    Emmanuel Vincent;Jon Barker;Shinji Watanabe;Jonathan Le Roux

  • Discriminatively trained recurrent neural networks for single-channel speech separation

    Felix Weninger;John R. Hershey;Jonathan Le Roux;Bjorn Schuller

  • Phase Processing for Single-Channel Speech Enhancement: History and recent advances

    Timo Gerkmann;Martin Krawczyk-Becker;Jonathan Le Roux

  • WHAM!: Extending Speech Separation to Noisy Environments

    Gordon Wichern;Joe Antognini;Michael Flynn;Licheng Richard Zhu

  • Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation

    Zhong-Qiu Wang;Jonathan Le Roux;John R. Hershey

  • Full-capacity unitary recurrent neural networks

    Scott Wisdom;Thomas Powers;John R. Hershey;Jonathan Le Roux

  • Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error

    E. McDermott;T.J. Hazen;J. Le Roux;A. Nakamura

  • Alternative Objective Functions for Deep Clustering

    Zhong-Qiu Wang;Jonathan Le Roux;John R. Hershey

  • Separation of a monaural audio signal into harmonic/percussive components by complementary diffusion on spectrogram

    Nobutaka Ono;Kenichi Miyamoto;Jonathan Le Roux;Hirokazu Kameoka

  • Deep clustering and conventional networks for music separation: Stronger together

    Yi Luo;Zhuo Chen;John R. Hershey;Jonathan Le Roux

  • Universal Sound Separation

    Ilya Kavalerov;Scott Wisdom;Hakan Erdogan;Brian Patton

  • Deep NMF for speech separation

    Jonathan Le Roux;John R. Hershey;Felix Weninger

  • End-to-End Speech Separation with Unfolded Iterative Phase Reconstruction

    Zhong-Qiu Wang;Jonathan Le Roux;DeLiang Wang;John R. Hershey

  • Streaming automatic speech recognition with the transformer model

    Niko Moritz;Takaaki Hori;Jonathan Le Roux

Frequent Co-Authors

John R. Hershey
John R. Hershey Google (United States)
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Hirokazu Kameoka
Hirokazu Kameoka NTT (Japan)
Shigeki Sagayama
Shigeki Sagayama University of Tokyo
Nobutaka Ono
Nobutaka Ono Tokyo Metropolitan University
Hakan Erdogan
Hakan Erdogan Google (United States)
Emmanuel Vincent
Emmanuel Vincent University of Lorraine
Felix Weninger
Felix Weninger Nuance Communications (United States)
Yanmin Qian
Yanmin Qian Shanghai Jiao Tong University
Alain de Cheveigné
Alain de Cheveigné École Normale Supérieure

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