World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
10602
World Ranking
7837
National Ranking
3390

Mo Yu 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 Mo Yu 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 128 publications — 18th percentile

18% of scientists in this discipline score the same or lower.

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

Mo Yu 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 Mo Yu sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Mo Yu is a researcher affiliated with IBM in the United States with a focus on computer science, particularly in artificial intelligence and related subfields. Their publication record spans a range of topics centered on machine learning, natural language processing, and human-computer interaction.

The scientist's recent papers include:

  • StoryBuddy: A Human-AI Collaborative Chatbot for Parent-Child Interactive Storytelling with Flexible Parental Involvement (2022) published in the CHI Conference on Human Factors in Computing Systems
  • On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models? (2022) published in the Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • CASS (2021) published in Proceedings of the ACM on Human-Computer Interaction
  • Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding (2022) published in Findings of the Association for Computational Linguistics: ACL 2022
  • Invariant Rationalization (2020) published in arXiv (Cornell University)

Mo Yu's frequent coauthors include:

  • Shiyu Chang
  • Xiangyang Mou
  • Xiaoxiao Guo
  • Dakuo Wang
  • Saloni Potdar

The main publication venues where Mo Yu's work appears frequently are:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Proceedings of the ACM on Human-Computer Interaction
  • Proceedings of the AAAI Conference on Artificial Intelligence

The primary fields of study for Mo Yu encompass computer science with a significant emphasis on artificial intelligence. Subfields receiving focused attention include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Management Science and Operations Research
  • Molecular Biology

Their main research topics cover a diverse set of areas, including:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • AI in Service Interactions
  • Expert finding and Q&A systems
  • Advanced Graph Neural Networks

Best Publications

  • A Structured Self-Attentive Sentence Embedding.

    Zhouhan Lin;Minwei Feng;Cicero Nogueira dos Santos;Mo Yu

  • Target-dependent Twitter Sentiment Classification

    Long Jiang;Mo Yu;Ming Zhou;Xiaohua Liu

  • Comparative Study of CNN and RNN for Natural Language Processing

    Wenpeng Yin;Katharina Kann;Mo Yu;Hinrich Schütze

  • Improving Lexical Embeddings with Semantic Knowledge

    Mo Yu;Mark Dredze

  • Improved Neural Relation Detection for Knowledge Base Question Answering

    Mo Yu;Wenpeng Yin;Kazi Saidul Hasan;Cícero Nogueira dos Santos

  • R 3 : Reinforced Ranker-Reader for Open-Domain Question Answering.

    Shuohang Wang;Mo Yu;Xiaoxiao Guo;Zhiguo Wang

  • One-Shot Relational Learning for Knowledge Graphs

    Wenhan Xiong;Mo Yu;Shiyu Chang;Xiaoxiao Guo

  • Differential Treatment for Stuff and Things: A Simple Unsupervised Domain Adaptation Method for Semantic Segmentation

    Zhonghao Wang;Mo Yu;Yunchao Wei;Rogerio Feris

  • Diverse Few-Shot Text Classification with Multiple Metrics

    Mo Yu;Xiaoxiao Guo;Jinfeng Yi;Shiyu Chang

  • Dilated Recurrent Neural Networks

    Shiyu Chang;Yang Zhang;Wei Han;Mo Yu

  • Image Super-Resolution via Dual-State Recurrent Networks

    Wei Han;Shiyu Chang;Ding Liu;Mo Yu

  • Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

    Kun Xu;Liwei Wang;Mo Yu;Yansong Feng

  • Improved Relation Extraction with Feature-Rich Compositional Embedding Models

    Matthew R. Gormley;Mo Yu;Mark Dredze

  • DAG-GNN: DAG Structure Learning with Graph Neural Networks

    Yue Yu;Jie Chen;Tian Gao;Mo Yu

  • Simple Question Answering by Attentive Convolutional Neural Network

    Wenpeng Yin;Mo Yu;Bing Xiang;Bowen Zhou

  • Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control

    Mo Yu;Shiyu Chang;Yang Zhang;Tommi S. Jaakkola

  • Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

    Shuohang Wang;Mo Yu;Jing Jiang;Wei Zhang

  • Improving Natural Language Inference Using External Knowledge in the Science Questions Domain

    Xiaoyan Wang;Pavan Kapanipathi;Ryan Musa;Mo Yu

  • Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader.

    Wenhan Xiong;Mo Yu;Shiyu Chang;Xiaoxiao Guo

  • Leveraging Sentence-level Information with Encoder LSTM for Semantic Slot Filling

    Gakuto Kurata;Bing Xiang;Bowen Zhou;Mo Yu

  • Sentence Embedding Alignment for Lifelong Relation Extraction.

    Hong Wang;Wenhan Xiong;Mo Yu;Xiaoxiao Guo

  • Invariant Rationalization

    Shiyu Chang;Yang Zhang;Mo Yu;Tommi Jaakkola

Frequent Co-Authors

Shiyu Chang
Shiyu Chang University of California, Santa Barbara
William Yang Wang
William Yang Wang University of California, Santa Barbara
Bowen Zhou
Bowen Zhou IBM (United States)
Bing Xiang
Bing Xiang Amazon (United States)
Gerald Tesauro
Gerald Tesauro IBM (United States)
Mark Dredze
Mark Dredze Johns Hopkins University
Kun Xu
Kun Xu Beijing University of Posts and Telecommunications
Jing Jiang
Jing Jiang Singapore Management University
Yue Zhang
Yue Zhang Westlake University

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