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9997
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Computer Science

D-Index
54
Citations
13565
World Ranking
4512
National Ranking
2113

Jundong Li 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 Jundong Li 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: 238 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Jundong Li 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 Jundong Li 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: 54 D-Index — 69th percentile

69% 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

  • 2025 - Research.com Rising Stars Award

Overview

Jundong Li is a researcher affiliated with the University of Virginia in the United States with a multidisciplinary focus integrating computer science and medicine. Their published work covers various domains including artificial intelligence, oncology, and information systems, with a particular emphasis on advanced graph neural networks and cancer diagnosis and treatment techniques.

The scientist's research spans several main fields:

  • Computer Science
  • Medicine

Within these fields, their subfields of study include:

  • Artificial Intelligence
  • Oncology
  • Reproductive Medicine
  • Information Systems
  • Computer Vision and Pattern Recognition

Key research topics associated with Jundong Li's publications feature:

  • Advanced Graph Neural Networks
  • Ovarian cancer diagnosis and treatment
  • Recommender Systems and Techniques
  • Topic Modeling
  • Complex Network Analysis Techniques
  • Ethics and Social Impacts of AI
  • Endometrial and Cervical Cancer Treatments

Their frequent collaborators include:

  • Yushun Dong
  • Song Wang
  • Chen Chen
  • Huan Liu
  • Binchi Zhang

Jundong Li's research has been disseminated through reputable publication venues. The venues where they have published most frequently are:

  • arXiv (Cornell University)
  • Journal of Clinical Oncology
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • Proceedings of the AAAI Conference on Artificial Intelligence

Representative recent publications include:

  • Self-Supervised Learning for Recommender Systems: A Survey (2023, IEEE Transactions on Knowledge and Data Engineering)
  • Line Graph Neural Networks for Link Prediction (2021, IEEE Transactions on Pattern Analysis and Machine Intelligence)
  • Camrelizumab Plus Apatinib in Patients With Advanced Cervical Cancer (CLAP): A Multicenter, Open-Label, Single-Arm, Phase II Trial (2020, Journal of Clinical Oncology)
  • Enhancing Social Recommendation With Adversarial Graph Convolutional Networks (2020, IEEE Transactions on Knowledge and Data Engineering)
  • Using machine learning to predict ovarian cancer (2020, International Journal of Medical Informatics)

Best Publications

  • Feature Selection: A Data Perspective

    Jundong Li;Kewei Cheng;Suhang Wang;Fred Morstatter

  • Feature Selection: A Data Perspective

    Jundong Li;Kewei Cheng;Suhang Wang;Fred Morstatter

  • Label Informed Attributed Network Embedding

    Xiao Huang;Jundong Li;Xia Hu

  • Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation

    Junliang Yu;Hongzhi Yin;Jundong Li;Qinyong Wang

  • Deep Anomaly Detection on Attributed Networks.

    Kaize Ding;Jundong Li;Rohit Bhanushali;Huan Liu

  • Self-Supervised Learning for Recommender Systems: A Survey

    Unknown

  • Attributed Network Embedding for Learning in a Dynamic Environment

    Jundong Li;Harsh Dani;Xia Hu;Jiliang Tang

  • Accelerated attributed network embedding

    Xiao Huang;Jundong Li;Xia Hu

  • Challenges of Feature Selection for Big Data Analytics

    Jundong Li;Huan Liu

  • A Survey of Learning Causality with Data: Problems and Methods

    Ruocheng Guo;Lu Cheng;Jundong Li;P. Richard Hahn

  • Radar: residual analysis for anomaly detection in attributed networks

    Jundong Li;Harsh Dani;Xia Hu;Huan Liu

  • Line Graph Neural Networks for Link Prediction.

    Lei Cai;Jundong Li;Jie Wang;Shuiwang Ji

  • Be More with Less: Hypergraph Attention Networks for Inductive Text Classification

    Kaize Ding;Jianling Wang;Jundong Li;Dingcheng Li

  • ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks

    Zhen Peng;Minnan Luo;Jundong Li;Huan Liu

  • Enhance social recommendation with adversarial graph convolutional networks

    Junliang Yu;Hongzhi Yin;Jundong Li;Min Gao

  • Attributed Network Embedding for Learning in a Dynamic Environment

    Jundong Li;Harsh Dani;Xia Hu;Jiliang Tang

  • TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark

    Shangbin Feng;Herun Wan;Ningnan Wang;Jundong Li

  • A Survey of Learning Causality with Data: Problems and Methods

    Ruocheng Guo;Lu Cheng;Jundong Li;P. Richard Hahn

  • Interactive Anomaly Detection on Attributed Networks

    Kaize Ding;Jundong Li;Huan Liu

  • Multi-label informed feature selection

    Ling Jian;Jundong Li;Kai Shu;Huan Liu

  • Using machine learning to predict ovarian cancer.

    Mingyang Lu;Zhenjiang Fan;Bin Xu;Lujun Chen

  • Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation

    Junliang Yu;Min Gao;Jundong Li;Hongzhi Yin

  • Unsupervised Streaming Feature Selection in Social Media

    Jundong Li;Xia Hu;Jiliang Tang;Huan Liu

  • Graph Prototypical Networks for Few-shot Learning on Attributed Networks

    Kaize Ding;Jianling Wang;Jundong Li;Kai Shu

  • TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark

    Shangbin Feng;Herun Wan;Ningnan Wang;Jundong Li

  • Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation

    Junwei Zhang;Min Gao;Junliang Yu;Lei Guo

Frequent Co-Authors

Huan Liu
Huan Liu Arizona State University
Xia Hu
Xia Hu Rice University
Jiliang Tang
Jiliang Tang Michigan State University
Qinghua Zheng
Qinghua Zheng Xi'an Jiaotong University
Hongzhi Yin
Hongzhi Yin University of Queensland
Osmar R. Zaïane
Osmar R. Zaïane University of Alberta
Yi Chang
Yi Chang Jilin University
Shuiwang Ji
Shuiwang Ji Texas A&M University
Suhang Wang
Suhang Wang Pennsylvania State University
Hanghang Tong
Hanghang Tong University of Illinois at Urbana-Champaign

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