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D-Index
40
Citations
8462
World Ranking
647
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227

Computer Science

D-Index
33
Citations
5673
World Ranking
12533
National Ranking
1537

Yu Wu 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 Yu Wu 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: 90 publications — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Yu Wu 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 Yu Wu 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: 33 D-Index — 13th percentile

13% 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

  • 2025 - Research.com Rising Stars Award

Overview

Yu Wu is affiliated with Microsoft Research Asia (China) and has a substantial body of work in the field of Computer Science, particularly focused on Artificial Intelligence and Signal Processing. Their research primarily addresses topics related to speech and audio processing, including speech recognition, synthesis, and spoken language understanding.

Their recent publications include:

  • "WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing" (2022), published in IEEE Journal of Selected Topics in Signal Processing
  • "SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing" (2022), featured in Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • "Large-Scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification" (2022), presented at ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing
  • "Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation" (2020), included in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Unispeech-Sat: Universal Speech Representation Learning With Speaker Aware Pre-Training" (2022), also at ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing

Yu Wu frequently collaborates with other researchers, with notable coauthors including Shujie Liu, Jinyu Li, Chengyi Wang, Sanyuan Chen, and Yao Qian. These collaborations reflect a consistent engagement with experts in related subfields of speech and audio processing.

The venues where Yu Wu's work is most often published encompass a range of conferences and journals with strong reputations in their domains:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Interspeech 2022
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Yu Wu's research covers several main and subfields of study, with publications categorized as follows:

  • Main fields: Computer Science
  • Subfields: Artificial Intelligence, Signal Processing

The scientist's main research topics include:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Speech and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and Dialogue Systems
  • Text and Document Classification Technologies

Best Publications

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

    Sanyuan Chen;Chengyi Wang;Zhengyang Chen;Yu Wu

  • Sequential Matching Network: A New Architecture for Multi-turn Response Selection in Retrieval-Based Chatbots

    Yu Wu;Wei Wu;Chen Xing;Ming Zhou

  • Topic Aware Neural Response Generation

    Chen Xing;Wei Wu;Yu Wu;Jie Liu

  • Template-Based Named Entity Recognition Using BART

    Leyang Cui;Yu Wu;Jian Liu;Sen Yang

  • Developing Real-Time Streaming Transformer Transducer for Speech Recognition on Large-Scale Dataset

    Xie Chen;Yu Wu;Zhenghao Wang;Shujie Liu

  • Hierarchical Recurrent Attention Network for Response Generation

    Chen Xing;Yu Wu;Wei Wu;Yalou Huang

  • Keyphrase Generation with Correlation Constraints

    Jun Chen;Xiaoming Zhang;Yu Wu;Zhao Yan

  • On the Comparison of Popular End-to-End Models for Large Scale Speech Recognition.

    Jinyu Li;Yu Wu;Yashesh Gaur;Chengyi Wang

  • Continuous Speech Separation with Conformer

    Sanyuan Chen;Yu Wu;Zhuo Chen;Jian Wu

  • Response Generation by Context-Aware Prototype Editing

    Yu Wu;Furu Wei;Shaohan Huang;Yunli Wang

  • MuTual: A Dataset for Multi-Turn Dialogue Reasoning

    Leyang Cui;Yu Wu;Shujie Liu;Yue Zhang

  • SpeechT5: Unified-Modal Encoder-Decoder Pre-training for Spoken Language Processing

    Junyi Ao;Rui Wang;Long Zhou;Shujie Liu

  • Topic Aware Neural Response Generation

    Chen Xing;Wei Wu;Yu Wu;Jie Liu

  • Curriculum Pre-training for End-to-End Speech Translation

    Chengyi Wang;Yu Wu;Shujie Liu;Ming Zhou

  • Hierarchical Recurrent Attention Network for Response Generation

    Chen Xing;Wei Wu;Yu Wu;Ming Zhou

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

    Zhengyang Chen;Sanyuan Chen;Yu Wu;Yao Qian

  • Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation

    Chengyi Wang;Yu Wu;Shujie Liu;Zhenglu Yang

  • SpeechLM: Enhanced Speech Pre-Training With Unpaired Textual Data

    Unknown

  • Microsoft Speaker Diarization System for the Voxceleb Speaker Recognition Challenge 2020

    Xiong Xiao;Naoyuki Kanda;Zhuo Chen;Tianyan Zhou

  • A Sequential Matching Framework for Multi-Turn Response Selection in Retrieval-Based Chatbots

    Yu Wu;Wei Wu;Chen Xing;Can Xu

  • UniSpeech-SAT: Universal Speech Representation Learning with Speaker Aware Pre-Training.

    Sanyuan Chen;Yu Wu;Chengyi Wang;Zhengyang Chen

  • Topic Augmented Neural Response Generation with a Joint Attention Mechanism.

    Chen Xing;Wei Wu;Yu Wu;Jie Liu

  • Neural Response Generation With Dynamic Vocabularies

    Yu Wu;Wei Wu;Dejian Yang;Can Xu

  • Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer

    Yunli Wang;Yu Wu;Lili Mou;Zhoujun Li

  • Response selection with topic clues for retrieval-based chatbots

    Yu Wu;Zhoujun Li;Wei Wu;Ming Zhou

Frequent Co-Authors

Ming Zhou
Ming Zhou Langboat Technology
Shujie Liu
Shujie Liu Microsoft Research Asia (China)
Jinyu Li
Jinyu Li Microsoft (United States)
Zhoujun Li
Zhoujun Li Beihang University
Furu Wei
Furu Wei Microsoft (United States)
Takuya Yoshioka
Takuya Yoshioka Microsoft (United States)
Naoyuki Kanda
Naoyuki Kanda Hitachi (Japan)
Yue Zhang
Yue Zhang Westlake University
Yifan Gong
Yifan Gong Microsoft (United States)
Wei-Ying Ma
Wei-Ying Ma Tsinghua University

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