World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
7145
World Ranking
7639
National Ranking
1005

Nan Tang 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 Nan Tang 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: 138 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

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

Nan Tang 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 Nan Tang 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Nan Tang is affiliated with the Qatar Computing Research Institute in Qatar and has contributed extensively to the field of computer science through numerous research publications. Their work is predominantly situated within computer science, with a strong focus on artificial intelligence, management science and operations research, information systems, computer vision and pattern recognition, and computer networks and communications.

The key research topics Nan Tang has addressed include:

  • Data Quality and Management
  • Topic Modeling
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques
  • Privacy-Preserving Technologies in Data
  • Scientific Computing and Data Management
  • Semantic Web and Ontologies

Nan Tang has co-authored numerous papers with several frequent collaborators. These include Guoliang Li, Ju Fan, Yuyu Luo, Chengliang Chai, and Xiaoyong Du.

The scientist has published substantially in a range of publication venues. Their most frequent outlets include:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • Proceedings of the ACM on Management of Data
  • The VLDB Journal
  • IEEE Transactions on Knowledge and Data Engineering

Among recent notable publications are the following:

  • "Natural Language to Visualization by Neural Machine Translation," 2021, IEEE Transactions on Visualization and Computer Graphics
  • "Learned cardinality estimation," 2021, Proceedings of the VLDB Endowment
  • "Deep learning for blocking in entity matching," 2021, Proceedings of the VLDB Endowment
  • "RPT," 2021, Proceedings of the VLDB Endowment
  • "Selective data acquisition in the wild for model charging," 2022, Proceedings of the VLDB Endowment

Best Publications

  • NADEEF: a commodity data cleaning system

    Michele Dallachiesa;Amr Ebaid;Ahmed Eldawy;Ahmed Elmagarmid

  • Graph pattern matching: from intractable to polynomial time

    Wenfei Fan;Jianzhong Li;Shuai Ma;Nan Tang

  • KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing

    Xu Chu;John Morcos;Ihab F. Ilyas;Mourad Ouzzani

  • Towards certain fixes with editing rules and master data

    Wenfei Fan;Jianzhong Li;Shuai Ma;Nan Tang

  • Detecting data errors: where are we and what needs to be done?

    Ziawasch Abedjan;Xu Chu;Dong Deng;Raul Castro Fernandez

  • BigDansing: A System for Big Data Cleansing

    Zuhair Khayyat;Ihab F. Ilyas;Alekh Jindal;Samuel Madden

  • DeepEye: Towards Automatic Data Visualization

    Yuyu Luo;Xuedi Qin;Nan Tang;Guoliang Li

  • Making data visualization more efficient and effective: a survey

    Xuedi Qin;Yuyu Luo;Nan Tang;Guoliang Li

  • DeepER - Deep Entity Resolution.

    Muhammad Ebraheem;Saravanan Thirumuruganathan;Shafiq R. Joty;Mourad Ouzzani

  • Distributed representations of tuples for entity resolution

    Muhammad Ebraheem;Saravanan Thirumuruganathan;Shafiq Joty;Mourad Ouzzani

  • Adding regular expressions to graph reachability and pattern queries

    Wenfei Fan;Wenfei Fan;Jianzhong Li;Shuai Ma;Nan Tang

  • Adding regular expressions to graph reachability and pattern queries

    Wenfei Fan;Jianzhong Li;Shuai Ma;Nan Tang

  • Interaction between Record Matching and Data Repairing

    Wenfei Fan;Shuai Ma;Nan Tang;Wenyuan Yu

  • Towards dependable data repairing with fixing rules

    Jiannan Wang;Nan Tang

  • Interaction between record matching and data repairing

    Wenfei Fan;Jianzhong Li;Shuai Ma;Nan Tang

  • Reinforcement Learning with Tree-LSTM for Join Order Selection

    Xiang Yu;Guoliang Li;Chengliang Chai;Nan Tang

  • The data civilizer system

    Dong Deng;Raul Castro Fernandez;Ziawasch Abedjan;Sibo Wang

  • Synthesizing entity matching rules by examples

    Rohit Singh;Venkata Vamsikrishna Meduri;Ahmed Elmagarmid;Samuel Madden

  • Natural Language to Visualization by Neural Machine Translation.

    Yuyu Luo;Nan Tang;Guoliang Li;Jiawei Tang

  • Raha: A Configuration-Free Error Detection System

    Mohammad Mahdavi;Ziawasch Abedjan;Raul Castro Fernandez;Samuel Madden

  • Seeping Semantics: Linking Datasets Using Word Embeddings for Data Discovery

    Raul Castro Fernandez;Essam Mansour;Abdulhakim A. Qahtan;Ahmed Elmagarmid

Frequent Co-Authors

Mourad Ouzzani
Mourad Ouzzani Qatar Computing Research Institute
Ahmed K. Elmagarmid
Ahmed K. Elmagarmid Qatar Computing Research Institute
Ihab F. Ilyas
Ihab F. Ilyas University of Waterloo
Wenfei Fan
Wenfei Fan University of Edinburgh
Jeffrey Xu Yu
Jeffrey Xu Yu Chinese University of Hong Kong
Jianzhong Li
Jianzhong Li Harbin Institute of Technology
Kam-Fai Wong
Kam-Fai Wong Chinese University of Hong Kong

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