World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
12591
World Ranking
4781
National Ranking
639

Daniel Zeng 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 Daniel Zeng 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: 464 publications — 91st percentile

91% of scientists in this discipline score the same or lower.

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

Daniel Zeng 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 Daniel Zeng 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: 53 D-Index — 67th percentile

67% of scientists in this discipline score the same or lower.

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

Overview

Daniel Zeng is a researcher affiliated with the Chinese Academy of Sciences in China, with a focus on computer science. Their work spans various subfields including artificial intelligence, modeling and simulation, statistical and nonlinear physics, economics and econometrics, and computer vision and pattern recognition.

Their research covers a range of topics, notably:

  • Topic Modeling
  • COVID-19 epidemiological studies
  • Advanced Graph Neural Networks
  • Complex Network Analysis Techniques
  • Sentiment Analysis and Opinion Mining
  • Advanced Text Analysis Techniques
  • COVID-19 Pandemic Impacts

Zeng's publication record includes contributions to various well-known venues such as arXiv (Cornell University), IEEE Intelligent Systems, bioRxiv (Cold Spring Harbor Laboratory), IEEE Transactions on Computational Social Systems, and the INFORMS Journal on Computing.

Among recent papers, the following works are notable:

  • Estimating the effective reproduction number of the 2019-nCoV in China, 2020, bioRxiv (Cold Spring Harbor Laboratory)
  • Equitable access to COVID-19 vaccines makes a life-saving difference to all countries, 2022, Nature Human Behaviour
  • Fusion of heterogeneous attention mechanisms in multi-view convolutional neural network for text classification, 2020, Information Sciences
  • A hybrid machine learning framework for analyzing human decision-making through learning preferences, 2020, Omega
  • Effect of heterogeneous risk perception on information diffusion, behavior change, and disease transmission, 2020, Physical Review E

Frequent coauthors working with Zeng include Qingpeng Zhang, Zhidong Cao, Linjing Li, Xiaolong Zheng, and Qiudan Li.

Best Publications

  • Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering

    Zan Huang;Hsinchun Chen;Daniel Zeng

  • Social Computing: From Social Informatics to Social Intelligence

    Fei-Yue Wang;Daniel Zeng;K.M. Carley;W. Mao

  • Social Media Analytics and Intelligence

    Daniel Zeng;Hsinchun Chen;R Lusch;Shu-Hsing Li

  • A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce

    Zan Huang;D. Zeng;Hsinchun Chen

  • COPLINK: managing law enforcement data and knowledge

    Hsinchun Chen;Daniel Zeng;Homa Atabakhsh;Wojciech Wyzga

  • Sentiment analysis of Chinese documents: From sentence to document level

    Changli Zhang;Daniel Zeng;Jiexun Li;Fei-Yue Wang

  • A comparison of collaborative-filtering algorithms for ecommerce

    Zan Huang;Daniel Zeng;Hsinchun Chen

  • Sentiment analysis of Chinese documents: From sentence to document level

    Unknown

  • CI Spider: a tool for competitive intelligence on the web

    Hsinchun Chen;Michael Chau;Daniel Zeng

  • The State-of-the-Art in Twitter Sentiment Analysis: A Review and Benchmark Evaluation

    David Zimbra;Ahmed Abbasi;Daniel Zeng;Hsinchun Chen

  • Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems

    Zan Huang;Daniel D. Zeng;Hsinchun Chen

  • Twitter Sentiment Analysis: A Bootstrap Ensemble Framework

    Ammar Hassan;Ahmed Abbasi;Daniel Zeng

  • Smart Cars on Smart Roads: An IEEE Intelligent Transportation Systems Society Update

    Fei-Yue Wang;Daniel Zeng;Liuqing Yang

  • Design and evaluation of a multi-agent collaborative Web mining system

    Michael Chau;Daniel Zeng;Hsinchun Chen;Michael Huang

  • A Study of the Human Flesh Search Engine: Crowd-Powered Expansion of Online Knowledge

    Fei-Yue Wang;Daniel Zeng;James A Hendler;Qingpeng Zhang

  • A survey on big data-driven digital phenotyping of mental health

    Yunji Liang;Xiaolong Zheng;Daniel Dajun Zeng;Daniel Dajun Zeng

  • Intelligence and security informatics for homeland security: information, communication, and transportation

    H. Chen;Fei-Yue Wang;D. Zeng

  • MetaSpider: Meta-Searching and Categorization on the Web

    Hsinchun Chen;Haiyan Fan;Michael Chau;Daniel Dajun Zeng

  • Social balance in signed networks

    Xiaolong Zheng;Daniel Zeng;Fei-Yue Wang

  • Personalized spiders for web search and analysis

    Michael Chau;Daniel Zeng;Hinchun Chen

  • Analyzing open-source software systems as complex networks

    Xiaolong Zheng;Daniel Zeng;Daniel Zeng;Huiqian Li;Feiyue Wang;Feiyue Wang

  • Multimodal Data Enhanced Representation Learning for Knowledge Graphs

    Zikang Wang;Linjing Li;Qiudan Li;Daniel Zeng

Frequent Co-Authors

Hsinchun Chen
Hsinchun Chen University of Arizona
Fei-Yue Wang
Fei-Yue Wang Chinese Academy of Sciences
Michael Chau
Michael Chau University of Hong Kong
Huimin Zhao
Huimin Zhao University of Illinois at Urbana-Champaign
Ahmed Abbasi
Ahmed Abbasi University of Notre Dame
Mark C. Thurmond
Mark C. Thurmond University of California, Davis
Christopher C. Yang
Christopher C. Yang Drexel University
Sudha Ram
Sudha Ram University of Arizona
Paul Jen-Hwa Hu
Paul Jen-Hwa Hu University of Utah
Kathleen M. Carley
Kathleen M. Carley Carnegie Mellon University

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