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Zheng-Hua Tan

Zheng-Hua Tan

Aalborg University
Denmark

D-Index & Metrics

Computer Science

D-Index
35
Citations
6263
World Ranking
11575
National Ranking
52

Zheng-Hua Tan 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 Zheng-Hua Tan 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: 325 publications — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Zheng-Hua Tan 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 Zheng-Hua Tan 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Zheng-Hua Tan is affiliated with Aalborg University in Denmark and has a research profile centered around computer science and engineering. Across their extensive publication record, they have made contributions particularly in the fields of signal processing and artificial intelligence, with additional work in electrical and electronic engineering and computational mechanics.

Their research topics cover several areas, including:

  • Speech and Audio Processing
  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Advanced Adaptive Filtering Techniques
  • Hearing Loss and Rehabilitation
  • Indoor and Outdoor Localization Technologies
  • Anomaly Detection Techniques and Applications

Zheng-Hua Tan has coauthored frequently with several researchers. The most common collaborators include Jesper Jensen, Jan Østergaard, Petar Popovski, Zhanyu Ma, and John Leth.

The scientist's work has been published in a variety of venues, with notable recurring appearances in:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Audio Speech and Language Processing
  • IEEE Access
  • Theory and Practice in Language Studies
  • Research Portal (King's College London)

Representative recent papers by Zheng-Hua Tan include:

  • Deep Spoken Keyword Spotting: An Overview, 2022, Research Portal (King's College London)
  • A new (2+1)-dimensional like-Harry-Dym equation with derivation and soliton solutions, 2025, Applied Mathematics Letters
  • Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • A Dual-Polarized Reconfigurable Reflectarray With a Thin Liquid Crystal Layer and 2-D Beam Scanning, 2023, IEEE Transactions on Antennas and Propagation
  • OSLNet: Deep Small-Sample Classification With an Orthogonal Softmax Layer, 2020, IEEE Transactions on Image Processing

The scientific outputs span multiple domains related to audio, speech, and signal technologies, reflecting a broad interest in both theoretical and applied aspects of these fields.

Best Publications

  • Permutation invariant training of deep models for speaker-independent multi-talker speech separation

    Dong Yu;Morten Kolbaek;Zheng-Hua Tan;Jesper Jensen

  • Multitalker Speech Separation With Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks

    Morten Kolbaek;Dong Yu;Zheng-Hua Tan;Jesper Jensen

  • Conditional Generative Adversarial Networks for Speech Enhancement and Noise-Robust Speaker Verification

    Daniel Michelsanti;Zheng-Hua Tan

  • An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation

    Daniel Michelsanti;Zheng-Hua Tan;Shi-Xiong Zhang;Yong Xu

  • Speech Intelligibility Potential of General and Specialized Deep Neural Network Based Speech Enhancement Systems

    Morten Kolbk;Zheng-Hua Tan;Jesper Jensen

  • Deep Spoken Keyword Spotting: An Overview

    Unknown

  • Adaptive protection combined with machine learning for microgrids

    Hengwei Lin;Kai Sun;Zheng Hua Tan;Chengxi Liu

  • On Loss Functions for Supervised Monaural Time-Domain Speech Enhancement

    Morten Kolbaek;Zheng-Hua Tan;Soren Holdt Jensen;Jesper Jensen

  • rVAD: An unsupervised segment-based robust voice activity detection method

    Zheng-Hua Tan;Achintya Kumar Sarkar;Najim Dehak

  • RedDots replayed: A new replay spoofing attack corpus for text-dependent speaker verification research

    Tomi Kinnunen;Sahidullah;Mauro Falcone;Luca Costantini

  • Decorrelation of Neutral Vector Variables: Theory and Applications

    Zhanyu Ma;Jing-Hao Xue;Arne Leijon;Zheng-Hua Tan

  • Low-Complexity Variable Frame Rate Analysis for Speech Recognition and Voice Activity Detection

    Zheng-Hua Tan;Børge Lindberg

  • Spoofing Detection in Automatic Speaker Verification Systems Using DNN Classifiers and Dynamic Acoustic Features

    Hong Yu;Zheng-Hua Tan;Zhanyu Ma;Rainer Martin

  • Automatic speech recognition on mobile devices and over communication networks

    Zheng-Hua Tan;Børge Lindberg

  • Automatic speech recognition over error-prone wireless networks☆

    Zheng-Hua Tan;Paul Dalsgaard;Børge Lindberg

  • DNN Filter Bank Cepstral Coefficients for Spoofing Detection

    Hong Yu;Zheng-Hua Tan;Yiming Zhang;Zhanyu Ma

  • Speech enhancement using Long Short-Term Memory based recurrent Neural Networks for noise robust Speaker Verification

    Morten Kolboek;Zheng-Hua Tan;Jesper Jensen

  • Advanced Dropout: A Model-free Methodology for Bayesian Dropout Optimization.

    Jiyang Xie;Zhanyu Ma;Jianjun Lei;Guoqiang Zhang

  • ASSOCIATIVE MEMORY USING SYNCHRONIZATION IN A CHAOTIC NEURAL NETWORK

    Unknown

  • Monaural Speech Enhancement Using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure

    Morten Kolbcek;Zheng-Hua Tan;Jesper Jensen

  • Integrated Spoofing Countermeasures and Automatic Speaker Verification: an Evaluation on ASVspoof 2015

    Sahidullah;Héctor Delgado;Massimiliano Todisco;Hong Yu

  • Nonintrusive Speech Intelligibility Prediction Using Convolutional Neural Networks

    Asger Heidemann Andersen;Jan Mark de Haan;Zheng-Hua Tan;Jesper Jensen

  • Refinement and validation of the binaural short time objective intelligibility measure for spatially diverse conditions

    Asger Heidemann Andersen;Jan Mark de Haan;Zheng-Hua Tan;Jesper Jensen

  • Monaural Speech Enhancement using Deep Neural Networks by Maximizing a Short-Time Objective Intelligibility Measure

    Morten Kolbæk;Zheng-Hua Tan;Jesper Jensen

  • Multi-talker Speech Separation with Utterance-level Permutation Invariant Training of Deep Recurrent Neural Networks

    Morten Kolbæk;Dong Yu;Zheng-Hua Tan;Jesper Jensen

Frequent Co-Authors

Jesper Jensen
Jesper Jensen Aalborg University
Søren Holdt Jensen
Søren Holdt Jensen University of Extremadura
Zhanyu Ma
Zhanyu Ma Beijing University of Posts and Telecommunications
Ramjee Prasad
Ramjee Prasad Aarhus University
Tomi Kinnunen
Tomi Kinnunen University of Eastern Finland
Jun Guo
Jun Guo Beijing University of Posts and Telecommunications
Mads Græsbøll Christensen
Mads Græsbøll Christensen Aalborg University
Jing-Hao Xue
Jing-Hao Xue University College London
Petar Popovski
Petar Popovski Aalborg University
Dong Yu
Dong Yu Tencent (China)

External Links

Personal website of Zheng-Hua Tan

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Best Scientists Citing Zheng-Hua Tan

Yu Tsao

Yu Tsao

Research Center for Information Technology Innovation, Academia Sinica

Publications: 61

Marc Delcroix

Marc Delcroix

NTT (Japan)

Publications: 58

Keisuke Kinoshita

Keisuke Kinoshita

NTT (Japan)

Publications: 52

Tomohiro Nakatani

Tomohiro Nakatani

NTT (Japan)

Publications: 45

Takuya Yoshioka

Takuya Yoshioka

Microsoft (United States)

Publications: 42

Shinji Watanabe

Shinji Watanabe

Carnegie Mellon University

Publications: 41

DeLiang Wang

DeLiang Wang

Chinese University of Hong Kong, Shenzhen

Publications: 39

Reinhold Haeb-Umbach

Reinhold Haeb-Umbach

University of Paderborn

Publications: 37

Jonathan Le Roux

Jonathan Le Roux

Mitsubishi Electric (United States)

Publications: 34

Yanmin Qian

Yanmin Qian

Shanghai Jiao Tong University

Publications: 33

Nima Mesgarani

Nima Mesgarani

Columbia University

Publications: 31

Haizhou Li

Haizhou Li

Chinese University of Hong Kong, Shenzhen

Publications: 28

Dong Yu

Dong Yu

Tencent (China)

Publications: 27

Zhanyu Ma

Zhanyu Ma

Beijing University of Posts and Telecommunications

Publications: 27

Jinyu Li

Jinyu Li

Microsoft (United States)

Publications: 27

John R. Hershey

John R. Hershey

Google (United States)

Publications: 25

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