World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6304
World Ranking
8914
National Ranking
3795

Dong 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 Dong 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: 342 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.

Dong 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 Dong 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Dong Wang is affiliated with the University of Notre Dame in the United States and has contributed extensively to the field of computer science, with a particular focus on artificial intelligence. Their research encompasses several subfields including sociology and political science, computer vision and pattern recognition, computer science applications, and electrical and electronic engineering.

Their work covers a range of topics, reflecting a multidisciplinary approach involving:

  • Topic Modeling
  • Mobile Crowdsensing and Crowdsourcing
  • Misinformation and Its Impacts
  • Anomaly Detection Techniques and Applications
  • Natural Language Processing Techniques
  • Human Mobility and Location-Based Analysis
  • Data-Driven Disease Surveillance

Dong Wang has authored numerous research papers, some of the recent notable publications include:

  • CovidSens: a vision on reliable social sensing for COVID-19, 2020, Artificial Intelligence Review
  • A Multimodal Misinformation Detector for COVID-19 Short Videos on TikTok, 2021, 2021 IEEE International Conference on Big Data (Big Data)
  • A Duo-generative Approach to Explainable Multimodal COVID-19 Misinformation Detection, 2022, Proceedings of the ACM Web Conference 2022
  • HC-COVID, 2022, Proceedings of the ACM on Human-Computer Interaction
  • Machine Learning Based Prediction of Enzymatic Degradation of Plastics Using Encoded Protein Sequence and Effective Feature Representation, 2023, Environmental Science & Technology Letters

Their frequent collaborators include researchers such as Lanyu Shang, Yang Zhang, Ziyi Kou, Huimin Zeng, and Zhenrui Yue, indicating a strong network of coauthorship within their research community.

Dong Wang's publications frequently appear in venues recognized within the computer science domain, including:

  • arXiv (Cornell University)
  • Knowledge-Based Systems
  • Proceedings of the ACM on Human-Computer Interaction
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • SSRN Electronic Journal

Their research contributions primarily advance knowledge in artificial intelligence and its applications, particularly focusing on the detection and analysis of misinformation, social sensing for public health, and machine learning techniques. This profile reflects a sustained scholarly output and engagement with interdisciplinary domains intersecting computer science and social sciences.

Best Publications

  • On truth discovery in social sensing: a maximum likelihood estimation approach

    Dong Wang;Lance Kaplan;Hieu Le;Tarek Abdelzaher

  • Relation Classification via Recurrent Neural Network

    Dongxu Zhang;Dong Wang

  • Using humans as sensors: an estimation-theoretic perspective

    Dong Wang;Tanvir Amin;Shen Li;Tarek Abdelzaher

  • Enzyme Discovery and Engineering for Sustainable Plastic Recycling.

    Baotong Zhu;Dong Wang;Na Wei

  • The Age of Social Sensing

    Dong Wang;Boleslaw K. Szymanski;Tarek Abdelzaher;Heng Ji

  • Social Sensing: Building Reliable Systems on Unreliable Data

    Dong Wang;Tarek Abdelzaher;Lance Kaplan

  • Recursive Fact-Finding: A Streaming Approach to Truth Estimation in Crowdsourcing Applications

    Dong Wang;Tarek Abdelzaher;Lance Kaplan;Charu C. Aggarwal

  • Click-through Prediction for Advertising in Twitter Timeline

    Cheng Li;Yue Lu;Qiaozhu Mei;Dong Wang

  • On Credibility Estimation Tradeoffs in Assured Social Sensing

    Dong Wang;L. Kaplan;T. Abdelzaher;C. C. Aggarwal

  • CovidSens: a vision on reliable social sensing for COVID-19.

    Tahmid Rashid;Dong Wang

  • Efficient Graph Similarity Search Over Large Graph Databases

    Weiguo Zheng;Lei Zou;Xiang Lian;Dong Wang

  • Maximum likelihood analysis of conflicting observations in social sensing

    Dong Wang;Lance Kaplan;Tarek F. Abdelzaher

  • On Scalable and Robust Truth Discovery in Big Data Social Media Sensing Applications

    Daniel Zhang;Dong Wang;Nathan Vance;Yang Zhang

  • Shedding light on “Black Box” machine learning models for predicting the reactivity of HO radicals toward organic compounds

    Shifa Zhong;Kai Zhang;Dong Wang;Huichun Zhang

  • CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding

    Dong Wang;Ning Ding;Piji Li;Haitao Zheng

  • Chinese song iambics generation with neural attention-based model

    Qixin Wang;Tianyi Luo;Dong Wang;Chao Xing

  • Towards Cyber-Physical Systems in Social Spaces: The Data Reliability Challenge

    Shiguang Wang;Dong Wang;Lu Su;Lance Kaplan

  • FairFL: A Fair Federated Learning Approach to Reducing Demographic Bias in Privacy-Sensitive Classification Models

    Daniel Yue Zhang;Ziyi Kou;Dong Wang

  • Flexible and Creative Chinese Poetry Generation Using Neural Memory

    Jiyuan Zhang;Yang Feng;Dong Wang;Yang Wang

  • Exploitation of Physical Constraints for Reliable Social Sensing

    Dong Wang;Tarek Abdelzaher;Lance Kaplan;Raghu Ganti

  • On robust truth discovery in sparse social media sensing

    Daniel Yue Zhang;Rungang Han;Dong Wang;Chao Huang

  • CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications

    Daniel Zhang;Yang Zhang;Qi Li;Thomas Plummer

  • On Bayesian interpretation of fact-finding in information networks

    Dong Wang;Tarek Abdelzaher;Hossein Ahmadi;Jeff Pasternack

  • A Real-Time and Non-Cooperative Task Allocation Framework for Social Sensing Applications in Edge Computing Systems

    Daniel Zhang;Yue Ma;Yang Zhang;Suwen Lin

  • A Duo-generative Approach to Explainable Multimodal COVID-19 Misinformation Detection

    Unknown

  • Graph similarity search with edit distance constraint in large graph databases

    Weiguo Zheng;Lei Zou;Xiang Lian;Dong Wang

  • Cooperative-Competitive Task Allocation in Edge Computing for Delay-Sensitive Social Sensing

    Daniel Zhang;Yue Ma;Chao Zheng;Yang Zhang

Frequent Co-Authors

Tarek Abdelzaher
Tarek Abdelzaher University of Illinois at Urbana-Champaign
Lance Kaplan
Lance Kaplan United States Army Research Laboratory
Charu C. Aggarwal
Charu C. Aggarwal IBM (United States)
Dongyan Zhao
Dongyan Zhao Peking University
Nitesh V. Chawla
Nitesh V. Chawla University of Notre Dame
Heng Ji
Heng Ji University of Illinois at Urbana-Champaign
Boleslaw K. Szymanski
Boleslaw K. Szymanski Rensselaer Polytechnic Institute
Lu Su
Lu Su Purdue University West Lafayette
Amotz Bar-Noy
Amotz Bar-Noy City University of New York
Feng Zhao
Feng Zhao Microsoft (United States)

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