World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
41861
World Ranking
10421
National Ranking
4348

Xiaowei Xu 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 Xiaowei Xu 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: 107 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

Xiaowei Xu 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 Xiaowei Xu 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: 37 D-Index — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Overview

Xiaowei Xu is a researcher affiliated with the University of Arkansas at Little Rock in the United States. Their academic contributions span predominantly within the field of Computer Science, with a focused engagement on several interconnected subfields.

Their main areas of study include:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Molecular Biology
  • Radiology, Nuclear Medicine and Imaging
  • Immunology

Xiaowei Xu's research topics notably cover:

  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • COVID-19 diagnosis using AI
  • Aquaculture disease management and microbiota
  • Advanced Text Analysis Techniques
  • Biomedical Text Mining and Ontologies
  • Radiomics and Machine Learning in Medical Imaging

Recent papers authored or co-authored by Xiaowei Xu include:

  • "Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023" (2022), published in Nucleic Acids Research
  • "Tumor Mutation Burden and Immune Invasion Characteristics in Triple Negative Breast Cancer: Genome High-Throughput Data Analysis" (2021), published in Frontiers in Immunology
  • "Weakly-Supervised Cross-Domain Adaptation for Endoscopic Lesions Segmentation" (2020), published in IEEE Transactions on Circuits and Systems for Video Technology
  • "The associations between TMAO-related metabolites and blood lipids and the potential impact of rosuvastatin therapy" (2022), published in Lipids in Health and Disease
  • "How to Efficiently Adapt Large Segmentation Model(SAM) to Medical Images" (2023), published on arXiv (Cornell University)

Frequent publication venues for Xiaowei Xu feature:

  • arXiv (Cornell University)
  • IEEE Transactions on Circuits and Systems for Video Technology
  • Aquaculture
  • Multimedia Tools and Applications
  • SSRN Electronic Journal

The researcher has collaborated extensively with colleagues including:

  • Yiyu Shi
  • Jingfa Xiao
  • Xinrong Hu
  • Dewen Zeng
  • Jiahua Dong

Best Publications

  • A density-based algorithm for discovering clusters in large spatial Databases with Noise

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Xiaowei Xu

  • DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN

    Erich Schubert;Jörg Sander;Martin Ester;Hans Peter Kriegel

  • Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications

    Jörg Sander;Martin Ester;Hans-Peter Kriegel;Xiaowei Xu

  • A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Xiaowei Xu

  • SCAN: a structural clustering algorithm for networks

    Xiaowei Xu;Nurcan Yuruk;Zhidan Feng;Thomas A. J. Schweiger

  • Frequent term-based text clustering

    Florian Beil;Martin Ester;Xiaowei Xu

  • Incremental Clustering for Mining in a Data Warehousing Environment

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Michael Wimmer

  • A distribution-based clustering algorithm for mining in large spatial databases

    Xiaowei Xu;M. Ester;H.-P. Kriegel;J. Sander

  • Probabilistic memory-based collaborative filtering

    Kai Yu;A. Schwaighofer;V. Tresp;Xiaowei Xu

  • A Fast Parallel Clustering Algorithm for Large Spatial Databases

    Xiaowei Xu;Jochen Jäger;Hans-Peter Kriegel

  • Knowledge Discovery in Large Spatial Databases: Focusing Techniques for Efficient Class Identification

    Martin Ester;Hans-Peter Kriegel;Xiaowei Xu

  • Representative sampling for text classification using support vector machines

    Zhao Xu;Kai Yu;Volker Tresp;Xiaowei Xu

  • In silico drug repositioning: what we need to know.

    Zhichao Liu;Hong Fang;Kelly Reagan;Xiaowei Xu;Xiaowei Xu

  • A database interface for clustering in large spatial databases

    Martin Ester;Hans-Peter Kriegel;Xiaowei Xu

  • What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation

    Jiahua Dong;Yang Cong;Gan Sun;Bineng Zhong

  • Mining FDA drug labels using an unsupervised learning technique--topic modeling.

    Halil Bisgin;Zhichao Liu;Hong Fang;Xiaowei Xu;Xiaowei Xu

  • A Study of Homophily on Social Media

    Halil Bisgin;Nitin Agarwal;Xiaowei Xu

  • A structural approach for finding functional modules from large biological networks

    Mutlu Mete;Fusheng Tang;Xiaowei Xu;Nurcan Yuruk

  • Graph-based review spammer group detection

    Zhuo Wang;Songmin Gu;Xiangnan Zhao;Xiaowei Xu

  • Clustering for Mining in Large Spatial Databases.

    Martin Ester;Hans-Peter Kriegel;Jörg Sander;Xiaowei Xu

Frequent Co-Authors

Hans-Peter Kriegel
Hans-Peter Kriegel Ludwig-Maximilians-Universität München
Martin Ester
Martin Ester Simon Fraser University
Yang Cong
Yang Cong Chinese Academy of Sciences
Weida Tong
Weida Tong National Center for Toxicological Research
Jörg Sander
Jörg Sander University of Alberta
Kai Yu
Kai Yu Horizon Robotics Inc.
Gaohong He
Gaohong He Dalian University of Technology
Hong Fang
Hong Fang National Center for Toxicological Research
Volker Tresp
Volker Tresp Ludwig-Maximilians-Universität München
Ji Liu
Ji Liu Facebook (United States)

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