World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
7668
World Ranking
8366
National Ranking
1091

Yanmin Qian 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 Yanmin Qian 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: 363 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Yanmin Qian 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 Yanmin Qian 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Yanmin Qian is affiliated with Shanghai Jiao Tong University in China. Their research primarily focuses on fields within computer science, with notable work in artificial intelligence, signal processing, computer vision and pattern recognition, computational mechanics, and pharmacy.

The scientist's work extensively covers topics related to speech and audio processing. These include:

  • Speech Recognition and Synthesis
  • Speech and Audio Processing
  • Music and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and Dialogue Systems
  • Advanced Adaptive Filtering Techniques

Yanmin Qian has contributed to a substantial number of publications in prominent venues, indicating an active research profile. The most frequent publication venues consist of:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • 2022 13th International Symposium on Chinese Spoken Language Processing (ISCSLP)

Recent papers authored or co-authored by Yanmin Qian include:

  • "WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing," 2022, IEEE Journal of Selected Topics in Signal Processing
  • "Large-Scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification," 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • "Data Augmentation Using Deep Generative Models for Embedding Based Speaker Recognition," 2020, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Audio-Visual Deep Neural Network for Robust Person Verification," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing
  • "Modified Magnitude-Phase Spectrum Information for Spoofing Detection," 2021, IEEE/ACM Transactions on Audio Speech and Language Processing

The scientist frequently collaborates with a range of co-authors, including Zhengyang Chen, Wangyou Zhang, Shinji Watanabe, Chenda Li, and Shujie Liu, reflecting ongoing cooperative research efforts within their areas of specialization.

Best Publications

  • The Kaldi Speech Recognition Toolkit

    Daniel Povey;Arnab Ghoshal;Gilles Boulianne;Lukas Burget

  • WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

    Sanyuan Chen;Chengyi Wang;Zhengyang Chen;Yu Wu

  • Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition

    Yanmin Qian;Mengxiao Bi;Tian Tan;Kai Yu

  • Deep feature for text-dependent speaker verification

    Yuan Liu;Yanmin Qian;Nanxin Chen;Tianfan Fu

  • Generating exact lattices in the WFST framework

    Daniel Povey;Mirko Hannemann;Gilles Boulianne;Lukas Burget

  • Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition

    Xu Xiang;Shuai Wang;Houjun Huang;Yanmin Qian

  • Reshaping deep neural network for fast decoding by node-pruning

    Tianxing He;Yuchen Fan;Yanmin Qian;Tian Tan

  • Multi-task learning for text-dependent speaker verification.

    Nanxin Chen;Yanmin Qian;Kai Yu

  • Recognizing Multi-talker Speech with Permutation Invariant Training

    Dong Yu;Xuankai Chang;Yanmin Qian

  • Wespeaker: A Research and Production Oriented Speaker Embedding Learning Toolkit

    Unknown

  • MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition

    Xuankai Chang;Wangyou Zhang;Yanmin Qian;Jonathan Le Roux

  • CUED-RNNLM — An open-source toolkit for efficient training and evaluation of recurrent neural network language models

    X. Chen;X. Liu;Y. Qian;M. J. F. Gales

  • Deep Extractor Network for Target Speaker Recovery From Single Channel Speech Mixtures

    Jun Wang;Jie Chen;Dan Su;Lianwu Chen

  • Robust deep feature for spoofing detection - the SJTU system for ASVspoof 2015 challenge.

    Nanxin Chen;Yanmin Qian;Heinrich Dinkel;Bo Chen

  • End-To-End Multi-Speaker Speech Recognition With Transformer

    Xuankai Chang;Wangyou Zhang;Yanmin Qian;Jonathan Le Roux

  • Overview of BTAS 2016 speaker anti-spoofing competition

    P. Korshunov;S. Marcel;H. Muckenhirn;A. R. Goncalves

  • Large-scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification.

    Zhengyang Chen;Sanyuan Chen;Yu Wu;Yao Qian

  • Past review, current progress, and challenges ahead on the cocktail party problem

    Yan-min Qian;Chao Weng;Xuan-kai Chang;Shuai Wang

  • Deep features for automatic spoofing detection

    Yanmin Qian;Nanxin Chen;Kai Yu

  • Cluster adaptive training for deep neural network

    Tian Tan;Yanmin Qian;Maofan Yin;Yimeng Zhuang

  • Single-channel multi-talker speech recognition with permutation invariant training

    Yanmin Qian;Xuankai Chang;Dong Yu

  • Very deep convolutional neural networks for robust speech recognition

    Yanmin Qian;Philip C Woodland

Frequent Co-Authors

Kai Yu
Kai Yu Shanghai Jiao Tong University
Dong Yu
Dong Yu Tencent (China)
Philip C. Woodland
Philip C. Woodland University of Cambridge
Mark J. F. Gales
Mark J. F. Gales University of Cambridge
Shinji Watanabe
Shinji Watanabe Carnegie Mellon University
Marc Delcroix
Marc Delcroix NTT (Japan)
Jonathan Le Roux
Jonathan Le Roux Mitsubishi Electric (United States)
Reinhold Haeb-Umbach
Reinhold Haeb-Umbach University of Paderborn

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