World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
5830
World Ranking
10274
National Ranking
4313

Ye-Yi Wang 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 Ye-Yi Wang 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: 120 publications — 15th percentile

15% of scientists in this discipline score the same or lower.

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

Ye-Yi Wang 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 Ye-Yi Wang 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Ye-Yi Wang is a researcher affiliated with Microsoft in the United States. Their work primarily falls within the field of Computer Science, with a focus on Artificial Intelligence, Computer Vision and Pattern Recognition, and General Social Sciences as subfields of study.

The main topics of Ye-Yi Wang's research include:

  • Text and Document Classification Technologies
  • Topic Modeling
  • Multimodal Machine Learning Applications
  • Natural Language Processing Techniques
  • Computational and Text Analysis Methods

Ye-Yi Wang has contributed to several publications, notably in venues such as arXiv (Cornell University) and the Proceedings of the ACM Web Conference 2022. Recent papers include:

  • Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification, 2022, Proceedings of the ACM Web Conference 2022
  • Metadata-Induced Contrastive Learning for Zero-Shot Multi-Label Text Classification, 2022, arXiv (Cornell University)
  • Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding, 2023, arXiv (Cornell University)

The researcher collaborates frequently with several coauthors, including:

  • Z. Shen
  • Chieh-Han Wu
  • Junheng Hao
  • Kuansan Wang
  • Jiawei Han

These collaborations and publication venues indicate a focus on text classification technologies and contrastive learning methods applied to multi-label and scientific literature domains. The recent work reflects an emphasis on zero-shot and multi-task learning approaches, addressing challenges related to understanding and categorizing large, complex datasets without extensive labeled data.

Best Publications

  • Multi-Domain Joint Semantic Frame Parsing Using Bi-Directional RNN-LSTM.

    Dilek Hakkani-Tür;Gokhan Tur;Asli Celikyilmaz;Yun-Nung Chen

  • Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval

    Xiaodong Liu;Jianfeng Gao;Xiaodong He;Li Deng

  • Learning query intent from regularized click graphs

    Xiao Li;Ye-Yi Wang;Alex Acero

  • Decoding Algorithm in Statistical Machine Translation

    Ye-Yi Wang;Alex Waibel

  • Is word error rate a good indicator for spoken language understanding accuracy

    Ye-Yi Wang;A. Acero;C. Chelba

  • Statistical classifiers for spoken language understanding and command/control scenarios

    Alejandro Acero;Ciprian Chelba;YeYi Wang;Leon Wong

  • Spoken language understanding

    Ye-Yi Wang;Li Deng;A. Acero

  • Use of a unified language model

    Xuedong D. Huang;Milind V. Mahajan;Ye-Yi Wang;Xiaolong Mou

  • A system for automatically annotating training data for a natural language understanding system

    Alejandro Acero;Ye-Yi Wang;Leon Wong

  • Extracting structured information from user queries with semi-supervised conditional random fields

    Xiao Li;Ye-Yi Wang;Alex Acero

  • Creating a language model for a language processing system

    Xuedong D. Huang;Milind V. Mahajan;Ye-Yi Wang;Xiaolong Mou

  • An introduction to voice search

    Ye-Yi Wang;Dong Yu;Yun-Cheng Ju;A. Acero

  • System for using statistical classifiers for spoken language understanding

    Alejandro Acero;Ciprian Chelba;Ye-Yi Wang;Leon Wong

  • Intent detection using semantically enriched word embeddings

    Joo-Kyung Kim;Gokhan Tur;Asli Celikyilmaz;Bin Cao

  • A unified context-free grammar and n-gram model for spoken language processing

    Ye-Yi Wang;M. Mahajan;Xuedong Huang

  • System with composite statistical and rules-based grammar model for speech recognition and natural language understanding

    Ye-Yi Wang;Alejandro Acero;Ciprian Chelba

  • Discriminative models for spoken language understanding.

    Ye-Yi Wang;Alex Acero

  • Template concatenation for capturing multiple concepts in a voice query

    Yun-Cheng Ju;Wei Wu;Ye-Yi Wang;Xiao Li

  • An Integrative and Discriminative Technique for Spoken Utterance Classification

    S. Yaman;Li Deng;Dong Yu;Ye-Yi Wang

  • Automated Directory Assistance System - from Theory to Practice

    Dong Yu;Yun-Cheng Ju;Ye-Yi Wang;Geoffrey Zweig

Frequent Co-Authors

Alejandro Acero
Alejandro Acero Apple (United States)
Li Deng
Li Deng Citadel
Dong Yu
Dong Yu Tencent (China)
Xuedong Huang
Xuedong Huang Microsoft (United States)
Kuansan Wang
Kuansan Wang Microsoft (United States)
Ciprian Chelba
Ciprian Chelba Google (United States)
Dilek Hakkani-Tur
Dilek Hakkani-Tur University of Illinois at Urbana-Champaign
Jianfeng Gao
Jianfeng Gao Microsoft (United States)
Gokhan Tur
Gokhan Tur Amazon (United States)
Hsiao-Wuen Hon
Hsiao-Wuen Hon Microsoft Research Asia (China)

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