World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
46
Citations
12847
World Ranking
6703
National Ranking
2960

Michael L. Seltzer 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 L. Seltzer 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: 175 publications — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Michael L. Seltzer 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 L. Seltzer 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: 46 D-Index — 53rd percentile

53% of scientists in this discipline score the same or lower.

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

Overview

Michael L. Seltzer is affiliated with Facebook in the United States and has contributed to research primarily within the field of Computer Science. Their scholarly work spans several subfields, including Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Mechanical Engineering, and Electrical and Electronic Engineering.

The main topics that Michael L. Seltzer has focused on are diverse and include Speech Recognition and Synthesis, Natural Language Processing Techniques, Topic Modeling, Speech and Dialogue Systems, Speech and Audio Processing, Music and Audio Processing, and Control Systems in Engineering.

Michael L. Seltzer has published extensively, with a significant number of papers featured in well-known venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Interspeech 2022
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • The Journal of the Acoustical Society of America
  • Encyclopedia of Social Work

Some of the recent publications are:

  • "Streaming parallel transducer beam search with fast slow cascaded encoders", 2022, Interspeech 2022
  • "Evaluating User Perception of Speech Recognition System Quality with Semantic Distance Metric", 2022, Interspeech 2022
  • "Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding", 2021, arXiv (Cornell University)
  • "Deliberation Model for On-Device Spoken Language Understanding", 2022, Interspeech 2022
  • "Weak-Attention Suppression For Transformer Based Speech Recognition", 2020, arXiv (Cornell University)

Throughout their career, Michael L. Seltzer has collaborated frequently with several coauthors including:

  • Ozlem Kalinli
  • Christian Fuegen
  • Duc Le
  • Jay Mahadeokar
  • Yangyang Shi

Best Publications

  • Recent advances in deep learning for speech research at Microsoft

    Li Deng;Jinyu Li;Jui-Ting Huang;Kaisheng Yao

  • A study on data augmentation of reverberant speech for robust speech recognition

    Tom Ko;Vijayaditya Peddinti;Daniel Povey;Michael L. Seltzer

  • An investigation of deep neural networks for noise robust speech recognition

    Michael L. Seltzer;Dong Yu;Yongqiang Wang

  • Achieving Human Parity in Conversational Speech Recognition

    Wayne Xiong;Jasha Droppo;Xuedong Huang;Frank Seide

  • Binary Coding of Speech Spectrograms Using a Deep Auto-encoder

    Li Deng;Michael L. Seltzer;Dong Yu;Alex Acero

  • An Introduction to Computational Networks and the Computational Network Toolkit

    Dong Yu;Adam Eversole;Mike Seltzer;Kaisheng Yao

  • Improved Bottleneck Features Using Pretrained Deep Neural Networks.

    Dong Yu;Michael L. Seltzer

  • Multi-task learning in deep neural networks for improved phoneme recognition

    Michael L. Seltzer;Jasha Droppo

  • Reconstruction of missing features for robust speech recognition

    Bhiksha Raj;Michael L. Seltzer;Richard M. Stern

  • The microsoft 2016 conversational speech recognition system

    W. Xiong;J. Droppo;X. Huang;F. Seide

  • CROWDMOS: An approach for crowdsourcing mean opinion score studies

    Flavio Ribeiro;Dinei Florencio;Cha Zhang;Michael Seltzer

  • Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks

    Dong Yu;Michael L. Seltzer;Jinyu Li;Jui-Ting Huang

  • Toward Human Parity in Conversational Speech Recognition

    Wayne Xiong;Jasha Droppo;Xuedong Huang;Frank Seide

  • Transformer-Based Acoustic Modeling for Hybrid Speech Recognition

    Yongqiang Wang;Abdelrahman Mohamed;Due Le;Chunxi Liu

  • A Bayesian Classifier for Spectrographic Mask Estimation for Missing Feature Speech Recognition

    Michael L. Seltzer;Bhiksha Raj;Richard M. Stern

  • Deep beamforming networks for multi-channel speech recognition

    Xiong Xiao;Shinji Watanabe;Hakan Erdogan;Liang Lu

  • Singular value decomposition based low-footprint speaker adaptation and personalization for deep neural network

    Jian Xue;Jinyu Li;Dong Yu;Mike Seltzer

  • Likelihood-maximizing beamforming for robust hands-free speech recognition

    M.L. Seltzer;B. Raj;R.M. Stern

  • Speech Processing for Digital Home Assistants: Combining signal processing with deep-learning techniques

    Reinhold Haeb-Umbach;Shinji Watanabe;Tomohiro Nakatani;Michiel Bacchiani

  • Deep neural network features and semi-supervised training for low resource speech recognition

    Samuel Thomas;Michael L. Seltzer;Kenneth Church;Hynek Hermansky

  • A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition

    Aren Jansen;Emmanuel Dupoux;Sharon Goldwater;Mark Johnson

Frequent Co-Authors

Ivan Tashev
Ivan Tashev Microsoft (United States)
Dong Yu
Dong Yu Tencent (China)
Alejandro Acero
Alejandro Acero Apple (United States)
John Krumm
John Krumm Microsoft (United States)
Jasha Droppo
Jasha Droppo Amazon (United States)
Bhiksha Raj
Bhiksha Raj Carnegie Mellon University
Richard M. Stern
Richard M. Stern Carnegie Mellon University
Jinyu Li
Jinyu Li Microsoft (United States)
Yifan Gong
Yifan Gong Microsoft (United States)
Frank Seide
Frank Seide Microsoft (United States)

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