World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
10620
World Ranking
6411
National Ranking
853

Shujie Liu 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 Shujie Liu 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: 224 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

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

Shujie Liu 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 Shujie Liu 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Shujie Liu is affiliated with Microsoft Research Asia (China) and has an extensive publication record in the fields of computer science and engineering. The research focus primarily spans artificial intelligence and signal processing, with a significant number of works addressing speech recognition and synthesis, music and audio processing, and natural language processing techniques.

The scientist's work has been published in several key venues, frequently contributing to:

  • arXiv (Cornell University)
  • ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • Interspeech 2022
  • SSRN Electronic Journal
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Shujie Liu has collaborated extensively with other researchers, including Jinyu Li, Long Zhou, Furu Wei, Sanyuan Chen, and Chengyi Wang. These frequent coauthors highlight a collaborative approach in advancing research within related domains.

The main research topics covered by Shujie Liu's work include:

  • Speech Recognition and Synthesis
  • Music and Audio Processing
  • Speech and Audio Processing
  • Natural Language Processing Techniques
  • Topic Modeling
  • Speech and dialogue systems
  • Drilling and Well Engineering

Recent papers showcase contributions across various aspects of speech and code processing. Notable works include:

  • "WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing," 2022, published in IEEE Journal of Selected Topics in Signal Processing
  • "CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation," 2021, published on arXiv (Cornell University)
  • "Progress in Neural NLP: Modeling, Learning, and Reasoning," 2020, published in Engineering
  • "CodeBLEU: a Method for Automatic Evaluation of Code Synthesis," 2020, published on arXiv (Cornell University)
  • "Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers," 2023, published on arXiv (Cornell University)

The breadth of Shujie Liu's work is evident in the diversity of subfields, with publications spanning artificial intelligence, signal processing, mechanical engineering, ocean engineering, and mechanics of materials. This range indicates engagement with multiple technical dimensions within and adjacent to speech and language technologies.

Combined, this information depicts a researcher active in advancing computational methods for speech and language, supported by collaborations and frequent contributions to prominent conferences and journals in related scientific domains.

Best Publications

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

    Sanyuan Chen;Chengyi Wang;Zhengyang Chen;Yu Wu

  • Achieving Human Parity on Automatic Chinese to English News Translation

    Hany Hassan;Anthony Aue;Chang Chen;Vishal Chowdhary

  • Neural Speech Synthesis with Transformer Network.

    Naihan Li;Shujie Liu;Yanqing Liu;Sheng Zhao

  • GraphCodeBERT: Pre-training Code Representations with Data Flow

    Daya Guo;Shuo Ren;Shuai Lu;Zhangyin Feng

  • CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

    Shuai Lu;Daya Guo;Shuo Ren;Junjie Huang

  • CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

    Shuai Lu;Daya Guo;Shuo Ren;Junjie Huang

  • Machine Translation

    Unknown

  • Neural Codec Language Models are Zero-Shot Text to Speech Synthesizers

    Unknown

  • Progress in Neural NLP: Modeling, Learning, and Reasoning

    Ming Zhou;Nan Duan;Shujie Liu;Heung Yeung Shum

  • A Recursive Recurrent Neural Network for Statistical Machine Translation

    Shujie Liu;Nan Yang;Mu Li;Ming Zhou

  • CodeBLEU: a Method for Automatic Evaluation of Code Synthesis

    Shuo Ren;Daya Guo;Shuai Lu;Long Zhou

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

    Xie Chen;Yu Wu;Zhenghao Wang;Shujie Liu

  • Hierarchical Recurrent Neural Network for Document Modeling

    Rui Lin;Shujie Liu;Muyun Yang;Mu Li

  • Learning Entity Representation for Entity Disambiguation

    Zhengyan He;Shujie Liu;Mu Li;Ming Zhou

  • GraphCodeBERT: Pre-training Code Representations with Data Flow

    Daya Guo;Shuo Ren;Shuai Lu;Zhangyin Feng

  • Style Transfer as Unsupervised Machine Translation

    Zhirui Zhang;Shuo Ren;Shujie Liu;Jianyong Wang

  • Virtual View Reconstruction Using Temporal Information

    Shujie Liu;Philip A. Chou;Cha Zhang;Zhengyou Zhang

  • Bilingually-constrained Phrase Embeddings for Machine Translation

    Jiajun Zhang;Shujie Liu;Mu Li;Ming Zhou

  • 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

  • Joint Training for Neural Machine Translation Models with Monolingual Data

    Zhirui Zhang;Shujie Liu;Mu Li;Ming Zhou

  • MuTual: A Dataset for Multi-Turn Dialogue Reasoning

    Leyang Cui;Yu Wu;Shujie Liu;Yue Zhang

  • Close to Human Quality TTS with Transformer

    Naihan Li;Shujie Liu;Yanqing Liu;Sheng Zhao

  • Word Alignment Modeling with Context Dependent Deep Neural Network

    Nan Yang;Shujie Liu;Mu Li;Ming Zhou

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

    Chengyi Wang;Yu Wu;Shujie Liu;Ming Zhou

Frequent Co-Authors

Ming Zhou
Ming Zhou Langboat Technology
Yu Wu
Yu Wu Microsoft Research Asia (China)
Mu Li
Mu Li Amazon (United States)
Jinyu Li
Jinyu Li Microsoft (United States)
Furu Wei
Furu Wei Microsoft (United States)
Nan Duan
Nan Duan Microsoft Research Asia (China)
Takuya Yoshioka
Takuya Yoshioka Microsoft (United States)
Duyu Tang
Duyu Tang Fudan University
Shuai Ma
Shuai Ma Beihang University
Daxin Jiang
Daxin Jiang Microsoft (United States)

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