World's Best Scientists 2026 revealed!
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Computer Science
Germany
2023

D-Index & Metrics

Computer Science

D-Index
70
Citations
31968
World Ranking
1826
National Ranking
930

Biing-Hwang Juang 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 Biing-Hwang Juang 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: 331 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Biing-Hwang Juang 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 Biing-Hwang Juang 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: 70 D-Index — 87th percentile

87% 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

  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2013 - Fellow, National Academy of Inventors
  • 2004 - Member of the National Academy of Engineering For contributions to speech coding and speech recognition.
  • 1992 - IEEE Fellow For contributions to the theory of vector quantization and its application to coding and automatic recognition of speech.

Overview

Biing-Hwang Juang is affiliated with the Georgia Institute of Technology in the United States. Their primary field of study is Computer Science, with contributions that encompass several subfields including Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Human-Computer Interaction, and Control and Systems Engineering.

The research topics they have worked on include:

  • Speech and dialogue systems
  • Wireless Signal Modulation Classification
  • Speech Recognition and Synthesis
  • Topic Modeling
  • Hand Gesture Recognition Systems
  • Human Pose and Action Recognition
  • Human Motion and Animation

Recent papers authored or co-authored by Biing-Hwang Juang cover developments in deep learning and wireless communication technologies as well as voice authentication methods. Notable publications include:

  • "Deep Learning Enabled Semantic Communication Systems," 2021, IEEE Transactions on Signal Processing
  • "Deep Learning-Based End-to-End Wireless Communication Systems With Conditional GANs as Unknown Channels," 2020, IEEE Transactions on Wireless Communications
  • "Deep Learning Based End-to-End Wireless Communication Systems Without Pilots," 2021, IEEE Transactions on Cognitive Communications and Networking
  • "Active voice authentication," 2020, Digital Signal Processing
  • "Accretionary Learning With Deep Neural Networks With Applications," 2023, IEEE Transactions on Cognitive Communications and Networking

Frequent co-authors collaborating with Biing-Hwang Juang include Geoffrey Ye Li, Ruolin Su, Mingyu Chen, Ghassan AlRegib, and Hao Ye.

The scientist's work has been published most often in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Cognitive Communications and Networking
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Wireless Communications

Awards and recognitions received by Biing-Hwang Juang include:

  • Fellow, National Academy of Inventors (2013)
  • Member of the National Academy of Engineering (2004) for contributions to speech coding and speech recognition
  • IEEE Fellow (1992) for contributions to the theory of vector quantization and its application to coding and automatic recognition of speech

Best Publications

  • An introduction to hidden Markov models

    L. Rabiner;B. Juang

  • Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems

    Hao Ye;Geoffrey Ye Li;Biing-Hwang Juang

  • Deep Learning Enabled Semantic Communication Systems

    Huiqiang Xie;Zhijin Qin;Geoffrey Ye Li;Biing-Hwang Juang

  • Discriminative learning for minimum error classification (pattern recognition)

    B.-H. Juang;S. Katagiri

  • Minimum classification error rate methods for speech recognition

    Biing-Hwang Juang;Wu Hou;Chin-Hui Lee

  • Hidden Markov models for speech recognition

    B. H. Juang;L. R. Rabiner

  • Deep Reinforcement Learning Based Resource Allocation for V2V Communications

    Hao Ye;Geoffrey Ye Li;Biing-Hwang Fred Juang

  • Signal Processing in Cognitive Radio

    Jun Ma;G.Y. Li;Biing Hwang Juang

  • A vector quantization approach to speaker recognition

    F. Soong;A. Rosenberg;L. Rabiner;B. Juang

  • Line spectrum pair (LSP) and speech data compression

    F. Soong;B. Juang

  • The segmental K-means algorithm for estimating parameters of hidden Markov models

    B.-H. Juang;L.R. Rabiner

  • A probabilistic distance measure for hidden Markov models

    B.-H. Juang;L. R. Rabiner

  • Speech Dereverberation Based on Variance-Normalized Delayed Linear Prediction

    Tomohiro Nakatani;Takuya Yoshioka;Keisuke Kinoshita;Masato Miyoshi

  • On the use of bandpass liftering in speech recognition

    Biing-Hwang Juang;L. Rabiner;J. Wilpon

  • A study on speaker adaptation of the parameters of continuous density hidden Markov models

    C.-H. Lee;C.-H. Lin;B.-H. Juang

  • Mixture autoregressive hidden Markov models for speech signals

    Biing-Hwang Juang;L. Rabiner

  • Multiple stage vector quantization for speech coding

    Biing-Hwang Juang;A. Gray

  • Recognition of isolated digits using hidden Markov models with continuous mixture densities

    L. R. Rabiner;B.-H. Juang;S. E. Levinson;M. M. Sondhi

  • Recognition unit model training based on competing word and word string models

    Wu Chou;Biing-Hwang Juang

  • Maximum-likelihood estimation for mixture multivariate stochastic observations of Markov chains

    B.-H. Juang

  • Discriminative utterance verification for connected digits recognition

    M.G. Rahim;Chin-Hui Lee;Biing-Hwang Juang

Frequent Co-Authors

Chin-Hui Lee
Chin-Hui Lee Georgia Institute of Technology
Lawrence R. Rabiner
Lawrence R. Rabiner Rutgers, The State University of New Jersey
Jay G. Wilpon
Jay G. Wilpon Ai Wilpon Consulting LLC
Stephen E. Levinson
Stephen E. Levinson University of Illinois at Urbana-Champaign
Tatsuya Kawahara
Tatsuya Kawahara Kyoto University
Frank K. Soong
Frank K. Soong Microsoft Research Asia (China)
Aaron E. Rosenberg
Aaron E. Rosenberg AT&T (United States)
Kuansan Wang
Kuansan Wang Microsoft (United States)
Kuldip K. Paliwal
Kuldip K. Paliwal Griffith University
Richard Rose
Richard Rose Google (United States)

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