World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
67
Citations
16110
World Ranking
2214
National Ranking
1109

Michael Picheny 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 Michael Picheny 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: 251 publications — 63rd percentile

63% of scientists in this discipline score the same or lower.

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

Michael Picheny 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 Michael Picheny 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: 67 D-Index — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2001 - IEEE Fellow For contributions to speech recognition systems and products.

Overview

Michael Picheny is a researcher primarily affiliated with IBM in the United States. Their work spans the field of computer science with a strong focus on artificial intelligence and signal processing. They have contributed extensively to speech recognition, speech and audio processing, and related areas in machine learning.

The main fields of study in which Michael Picheny has published include:

  • Computer Science

Their subfields of study encompass:

  • Artificial Intelligence
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Experimental and Cognitive Psychology
  • Political Science and International Relations

Michael Picheny's research topics cover several key areas, such as:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Speech and Audio Processing
  • Multimodal Machine Learning Applications
  • Natural Language Processing Techniques
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning

The scientist has collaborated frequently with several co-authors, including:

  • Samuel Thomas
  • Brian Kingsbury
  • Cal Peyser
  • Tara N. Sainath
  • Andrew Rouditchenko

Michael Picheny's publication record includes papers in a variety of academic venues. The most frequently appearing venues are:

  • arXiv (Cornell University)
  • IEEE Signal Processing Magazine
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022

Selected recent publications by Michael Picheny include:

  • Multimodal Clustering Networks for Self-supervised Learning from Unlabeled Videos, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies, 2020, IEEE Signal Processing Magazine
  • Towards Measuring Fairness in Speech Recognition: Casual Conversations Dataset Transcriptions, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings, 2021, arXiv (Cornell University)
  • Twenty-Five Years of Evolution in Speech and Language Processing, 2023, IEEE Signal Processing Magazine

Michael Picheny has been recognized with the IEEE Fellow award in 2001 for contributions to speech recognition systems and products.

Best Publications

  • Speaking Clearly for the Hard of Hearing II: Acoustic Characteristics of Clear and Conversational Speech.

    Michael A. Picheny;Nathaniel I. Durlach;Louis D. Braida

  • Speaker adaptation of neural network acoustic models using i-vectors

    George Saon;Hagen Soltau;David Nahamoo;Michael Picheny

  • Speaking clearly for the hard of hearing I: Intelligibility differences between clear and conversational speech.

    Michael A. Picheny;Nathaniel I. Durlach;Louis D. Braida

  • Automatic indexing and aligning of audio and text using speech recognition

    Hamed A. Ellozy;Dimitri Kanevsky;Michelle Y. Kim;David Nahamoo

  • Deep Belief Networks using discriminative features for phone recognition

    Abdel-rahman Mohamed;Tara N. Sainath;George Dahl;Bhuvana Ramabhadran

  • English Conversational Telephone Speech Recognition by Humans and Machines

    George Saon;Gakuto Kurata;Tom Sercu;Kartik Audhkhasi

  • Constructing Markov model word baseforms from multiple utterances by concatenating model sequences for word segments

    Lalit Rai Bahl;Peter Vincent Desouza;Robert Leroy Mercer;Michael Alan Picheny

  • Automatic determination of labels and markov word models in a speech recognition system

    Peter F. Brown;Peter V. De Souza;David Nahomoo;Michael A. Picheny

  • Speech recognition apparatus having a speech coder outputting acoustic prototype ranks

    Lalit R. Bahl;Peter Vincent De Souza;Ponani S. Gopalakrishnan;Michael Alan Picheny

  • Semantic language modeling and confidence measurement

    Mark E. Epstein;Hakan Erdogan;Yuqing Gao;Michael A. Picheny

  • The metamorphic algorithm: a speaker mapping approach to data augmentation

    J.R. Bellegarda;P.V. de Souza;A. Nadas;D. Nahamoo

  • Speech recognition using noise-adaptive prototypes

    A. Nadas;D. Nahamoo;M.A. Picheny

  • Speech recognizer having a speech coder for an acoustic match based on context-dependent speech-transition acoustic models

    Lalit R. Bahl;Peter V. De Souza;Ponani S. Gopalakrishnan;Michael A. Picheny

  • Speech recognition using noise-adaptive prototypes

    A. Nadas;D. Nahamoo;M.A. Picheny

  • Multonic Markov word models for large vocabulary continuous speech recognition

    L.R. Bahl;J.R. Bellegarda;P.V. de Souza;P.S. Gopalakrishnan

  • Automatic generation of simple markov model stunted baseforms for words in a vocabulary

    Lalit Rai Bahl;Peter Vincent Desouza;Robert Leroy Mercer;Michael Alan Picheny

  • Large vocabulary natural language continuous speech recognition

    L.R. Bahl;R. Bakis;J. Bellegarda;P.F. Brown

  • Acoustic Markov models used in the Tangora speech recognition system

    L.R. Bahl;P.F. Brown;P.V. de Souza;M.A. Picheny

  • Performance of the IBM large vocabulary continuous speech recognition system on the ARPA Wall Street Journal task

    L.R. Bahl;S. Balakrishnan-Aiyer;J.R. Bellgarda;M. Franz

  • Feneme-based Markov models for words

    Lalit R. Bahl;Peter V. deSouza;Robert L. Mercer;Michael A. Picheny

  • Method and apparatus for a communication device for use by a hearing impaired/mute or deaf person or in silent environments

    Peter Thomas Brunet;Abraham P. Ittycheriah;Chandrasekhar Narayanaswami;Michael Alan Picheny

Frequent Co-Authors

Lalit R. Bahl
Lalit R. Bahl Renaissance Technologies
David Nahamoo
David Nahamoo Pyron Inc.
Bhuvana Ramabhadran
Bhuvana Ramabhadran Google (United States)
George Saon
George Saon IBM (United States)
Robert Leroy Mercer
Robert Leroy Mercer Renaissance Technologies
Brian Kingsbury
Brian Kingsbury IBM (United States)
Hakan Erdogan
Hakan Erdogan Google (United States)
Ruhi Sarikaya
Ruhi Sarikaya Amazon (United States)
Samuel Thomas
Samuel Thomas IBM (United States)
Dimitri Kanevsky
Dimitri Kanevsky Google (United States)

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Related Online Degrees & Career Pathways

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Additionally, those drawn to data curation, analytics, or information management may benefit from online mlis programs (Master’s in Library and Information Science). These degrees prepare you for roles at the unique intersection of technology and information.

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