World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
9913
World Ranking
10000
National Ranking
4216

Xin Luna Dong 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 Xin Luna Dong 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: 131 publications — 19th percentile

19% of scientists in this discipline score the same or lower.

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

Xin Luna Dong 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 Xin Luna Dong 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.

Research.com Recognitions

  • 2018 - ACM Distinguished Member

Overview

Xin Luna Dong is affiliated with Facebook in the United States and has contributed extensively to research in computer science, with a focus on artificial intelligence and related subfields. Their work encompasses a variety of areas including topic modeling, advanced graph neural networks, natural language processing techniques, and recommender systems.

Their publication record includes a significant number of contributions across different venues, with notable frequent publication outlets such as:

  • arXiv (Cornell University)
  • Proceedings of the VLDB Endowment
  • SSRN Electronic Journal
  • Briefings in Bioinformatics
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Some recent papers authored or co-authored by Xin Luna Dong include:

  • "TCMPR: TCM Prescription Recommendation Based on Subnetwork Term Mapping and Deep Learning" (2022, BioMed Research International)
  • "HTINet2: herb-target prediction via knowledge graph embedding and residual-like graph neural network" (2024, Briefings in Bioinformatics)
  • "OA-Mine: Open-World Attribute Mining for E-Commerce Products with Weak Supervision" (2022, Proceedings of the ACM Web Conference 2022)
  • "A fault diagnosis method for rotating machinery with variable speed based on multi-feature fusion and improved ShuffleNet V2" (2022, Measurement Science and Technology)
  • "DRONet: effectiveness-driven drug repositioning framework using network embedding and ranking learning" (2022, Briefings in Bioinformatics)

The scientist's research topics focus on several core areas:

  • Topic Modeling
  • Advanced Graph Neural Networks
  • Natural Language Processing Techniques
  • Text and Document Classification Technologies
  • Recommender Systems and Techniques
  • Metabolomics and Mass Spectrometry Studies
  • Biomedical Text Mining and Ontologies

Co-authorship collaborations are an important aspect of their work. Frequent co-authors include:

  • Xuezhong Zhou
  • Kuo Yang
  • Yifan Xu
  • Xiaodan Liang
  • Qiang Zhu

The scientist has also authored a book titled An Introduction to Machine Learning in Quantitative Finance published by Advanced Textbooks in Mathematics in 2020, which has accumulated several citations.

Xun Luna Dong's contributions span over 60 publications in computer science, with a prominent emphasis on artificial intelligence, molecular biology, information systems, computer vision and pattern recognition, and surgery.

In recognition of professional achievements, they were awarded the ACM Distinguished Member title in 2018.

Best Publications

  • Knowledge vault: a web-scale approach to probabilistic knowledge fusion

    Xin Dong;Evgeniy Gabrilovich;Geremy Heitz;Wilko Horn

  • Similarity search for web services

    Xin Dong;Alon Halevy;Jayant Madhavan;Ema Nemes

  • Big Data Integration

    Xin Luna Dong;Divesh Srivastava

  • Reference reconciliation in complex information spaces

    Xin Dong;Alon Halevy;Jayant Madhavan

  • Integrating conflicting data: the role of source dependence

    Xin Luna Dong;Laure Berti-Equille;Divesh Srivastava

  • Data integration with uncertainty

    Xin Luna Dong;Alon Halevy;Cong Yu

  • Bootstrapping pay-as-you-go data integration systems

    Anish Das Sarma;Xin Dong;Alon Halevy

  • Truth finding on the deep web: is the problem solved?

    Xian Li;Xin Luna Dong;Kenneth Lyons;Weiyi Meng

  • Truth discovery and copying detection in a dynamic world

    Xin Luna Dong;Laure Berti-Equille;Divesh Srivastava

  • Data fusion: resolving data conflicts for integration

    Xin Luna Dong;Felix Naumann

  • The Piazza peer data management project

    Igor Tatarinov;Zachary Ives;Jayant Madhavan;Alon Halevy

  • A Platform for Personal Information Management and Integration.

    Xin Dong;Alon Y. Halevy

  • Indexing dataspaces

    Xin Dong;Alon Halevy

  • Less is more: selecting sources wisely for integration

    Xin Luna Dong;Barna Saha;Divesh Srivastava

  • From data fusion to knowledge fusion

    Xin Luna Dong;Evgeniy Gabrilovich;Geremy Heitz;Wilko Horn

  • Knowledge-based trust: estimating the trustworthiness of web sources

    Xin Luna Dong;Evgeniy Gabrilovich;Kevin Murphy;Van Dang

  • Incremental record linkage

    Anja Gruenheid;Xin Luna Dong;Divesh Srivastava

  • Linking temporal records

    Pei Li;Xin Luna Dong;Andrea Maurino;Divesh Srivastava

  • Global detection of complex copying relationships between sources

    Xin Luna Dong;Laure Berti-Equille;Yifan Hu;Divesh Srivastava

  • Fusing data with correlations

    Ravali Pochampally;Anish Das Sarma;Xin Luna Dong;Alexandra Meliou

  • OpenTag: Open Attribute Value Extraction from Product Profiles

    Guineng Zheng;Subhabrata Mukherjee;Xin Luna Dong;Feifei Li

  • Linking temporal records

    Pei Li;Xin Luna Dong;Andrea Maurino;Divesh Srivastava

  • Personal information management with SEMEX

    Yuhan Cai;Xin Luna Dong;Alon Halevy;Jing Michelle Liu

  • Data Integration and Machine Learning: A Natural Synergy

    Xin Luna Dong;Theodoros Rekatsinas

  • Data Integration and Machine Learning: A Natural Synergy

    Xin Luna Dong;Theodoros Rekatsinas

  • Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

    Namyong Park;Andrey Kan;Xin Luna Dong;Tong Zhao

  • Data X-Ray: A Diagnostic Tool for Data Errors

    Xiaolan Wang;Xin Luna Dong;Alexandra Meliou

  • Keys for graphs

    Wenfei Fan;Zhe Fan;Chao Tian;Xin Luna Dong

  • Characterizing and selecting fresh data sources

    Theodoros Rekatsinas;Xin Luna Dong;Divesh Srivastava

Frequent Co-Authors

Divesh Srivastava
Divesh Srivastava AT&T (United States)
Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Alon Halevy
Alon Halevy Facebook (United States)
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
Anish Das Sarma
Anish Das Sarma Google (United States)
Evgeniy Gabrilovich
Evgeniy Gabrilovich Google (United States)
Hannaneh Hajishirzi
Hannaneh Hajishirzi University of Washington
Weiyi Meng
Weiyi Meng Binghamton University
Felix Naumann
Felix Naumann Hasso Plattner Institute
Andrew McCallum
Andrew McCallum University of Massachusetts Amherst

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