World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
97
Citations
40642
World Ranking
422
National Ranking
234

Furu Wei 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 Furu Wei 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: 345 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Furu Wei 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 Furu Wei 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: 97 D-Index — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Overview

Furu Wei is affiliated with Microsoft in the United States and has contributed extensively to research in computer science, particularly within artificial intelligence and its related subfields. Their work spans a wide range of topics in the broader areas of natural language processing, computer vision, and signal processing.

The main fields of their research include:

  • Computer Science

Within this domain, the prominent subfields they focus on are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Information Systems
  • Electrical and Electronic Engineering

The topics covered in their publications highlight trends in:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Speech Recognition and Synthesis
  • Domain Adaptation and Few-Shot Learning
  • Speech and Audio Processing
  • Music and Audio Processing

Furu Wei has been prominently published in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • IEEE/ACM Transactions on Audio Speech and Language Processing

Their recent research papers include:

  • "Swin Transformer V2: Scaling Up Capacity and Resolution" (2022), published at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing" (2022), published in the IEEE Journal of Selected Topics in Signal Processing
  • "Unified language model pre-training for natural language understanding and generation" (2024), available on arXiv (Cornell University)
  • "BEiT: BERT Pre-Training of Image Transformers" (2021), on arXiv (Cornell University)
  • "MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers" (2020), also on arXiv (Cornell University)

Throughout their career, Furu Wei has worked collaboratively with a number of frequent co-authors, which include:

  • Shaohan Huang
  • Shuming Ma
  • Shujie Liu
  • Jinyu Li
  • Li Dong

This network of collaborators has contributed to the development and dissemination of research related to natural language understanding, multimodal learning, and speech technologies, reflecting a cross-disciplinary approach within computer science.

Best Publications

  • Swin Transformer V2: Scaling Up Capacity and Resolution

    Unknown

  • Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks

    Xiujun Li;Xi Yin;Chunyuan Li;Pengchuan Zhang

  • Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification

    Duyu Tang;Furu Wei;Nan Yang;Ming Zhou

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

    Sanyuan Chen;Chengyi Wang;Zhengyang Chen;Yu Wu

  • Unified Language Model Pre-training for Natural Language Understanding and Generation

    Li Dong;Nan Yang;Wenhui Wang;Furu Wei

  • LayoutLM: Pre-training of Text and Layout for Document Image Understanding

    Yiheng Xu;Minghao Li;Lei Cui;Shaohan Huang

  • Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification

    Li Dong;Furu Wei;Chuanqi Tan;Duyu Tang

  • VL-BERT: Pre-training of Generic Visual-Linguistic Representations

    Weijie Su;Xizhou Zhu;Yue Cao;Bin Li

  • BEiT: BERT Pre-Training of Image Transformers

    Hangbo Bao;Li Dong;Furu Wei

  • Gated Self-Matching Networks for Reading Comprehension and Question Answering

    Wenhui Wang;Nan Yang;Furu Wei;Baobao Chang

  • MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

    Wenhui Wang;Furu Wei;Li Dong;Hangbo Bao

  • LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking

    Unknown

  • Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach

    Xiaolong Wang;Furu Wei;Xiaohua Liu;Ming Zhou

  • Recognizing Named Entities in Tweets

    Xiaohua Liu;Shaodian Zhang;Furu Wei;Ming Zhou

  • Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks

    Unknown

  • Question Answering over Freebase with Multi-Column Convolutional Neural Networks

    Li Dong;Furu Wei;Ming Zhou;Ke Xu

  • Image as a Foreign Language: BEIT Pretraining for Vision and Vision-Language Tasks

    Unknown

  • LayoutLMv2: Multi-modal Pre-training for Visually-rich Document Understanding

    Yang Xu;Yiheng Xu;Tengchao Lv;Lei Cui

  • HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization

    Xingxing Zhang;Furu Wei;Ming Zhou

  • Context preserving dynamic word cloud visualization

    Weiwei Cui;Yingcai Wu;Shixia Liu;Furu Wei

  • SuperAgent: A Customer Service Chatbot for E-commerce Websites

    Lei Cui;Shaohan Huang;Furu Wei;Chuanqi Tan

  • Faithful to the Original: Fact Aware Neural Abstractive Summarization

    Ziqiang Cao;Furu Wei;Wenjie Li;Sujian Li

  • Context-Preserving, Dynamic Word Cloud Visualization

    Weiwei Cui;Yingcai Wu;Shixia Liu;Furu Wei

  • Pseudo-Masked Language Models for Unified Language Model Pre-Training

    Hangbo Bao;Li Dong;Furu Wei;Wenhui Wang

Frequent Co-Authors

Ming Zhou
Ming Zhou Langboat Technology
Li Dong
Li Dong Microsoft (United States)
Ke Xu
Ke Xu Beihang University
Sujian Li
Sujian Li Peking University
Wenjie Li
Wenjie Li Hong Kong Polytechnic University
Chuanqi Tan
Chuanqi Tan Tsinghua University
Ting Liu
Ting Liu Harbin Institute of Technology
Shixia Liu
Shixia Liu Tsinghua University
Yu Wu
Yu Wu Microsoft Research Asia (China)
Shuming Ma
Shuming Ma Peking University

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