World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
6428
World Ranking
9335
National Ranking
3965

Lifang He 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 Lifang He 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: 128 publications — 18th percentile

18% of scientists in this discipline score the same or lower.

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

Lifang He 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 Lifang He 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Lifang He is affiliated with Lehigh University in the United States and has an extensive publication record primarily in the field of Computer Science. Their research contributions span several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Molecular Biology, and Cognitive Neuroscience.

The scientist's work covers a range of topics with notable focus on advanced methodologies and applications such as:

  • Advanced Graph Neural Networks
  • Topic Modeling
  • Functional Brain Connectivity Studies
  • Complex Network Analysis Techniques
  • Stochastic Dynamics and Bifurcation
  • Probabilistic and Robust Engineering Design
  • Face and Expression Recognition

Lifang He has a significant number of scholarly articles published in respected venues. Some of the recent notable papers include:

  • "A Survey on Text Classification: From Traditional to Deep Learning," 2022, ACM Transactions on Intelligent Systems and Technology
  • "A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT," 2024, International Journal of Machine Learning and Cybernetics
  • "Multi-level Feature Learning for Contrastive Multi-view Clustering," 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • "Adversarial Attack and Defense on Graph Data: A Survey," 2022, IEEE Transactions on Knowledge and Data Engineering
  • "Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning," 2021, Information Sciences

The scientist has published extensively in venues such as arXiv with 59 publications, Proceedings of the AAAI Conference on Artificial Intelligence with 7 publications, IEEE Transactions on Knowledge and Data Engineering with 6 publications, IEEE Transactions on Neural Networks and Learning Systems with 4 publications, and Physica Scripta with 4 publications.

Lifang He frequently collaborates with other researchers, coauthoring with individuals including Philip S. Yu, Hao Peng, Lichao Sun, Xiaorong Pu, and Yazhou Ren.

Best Publications

  • 2014 IEEE International Conference on Data Mining

    Aleksandr Aravkin;Aurelie Lozano;Ronny Luss;Prabhajan Kambadur

  • Multi-level Feature Learning for Contrastive Multi-view Clustering

    Unknown

  • A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT

    Unknown

  • Multiple incomplete views clustering via weighted nonnegative matrix factorization with L 2,1 regularization

    Weixiang Shao;Lifang He;Philip S. Yu

  • Deep learning for drug repurposing: Methods, databases, and applications

    Unknown

  • Dynamic graph convolutional network for long-term traffic flow prediction with reinforcement learning

    Hao Peng;Bowen Du;Mingsheng Liu;Mingzhe Liu

  • KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning

    Ye Liu;Yao Wan;Lifang He;Hao Peng

  • SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism

    Qingyun Sun;Jianxin Li;Hao Peng;Jia Wu

  • Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification

    Hao Peng;Jianxin Li;Senzhang Wang;Lihong Wang

  • A robust least squares support vector machine for regression and classification with noise

    Xiaowei Yang;Liangjun Tan;Lifang He

  • A Linear Support Higher-Order Tensor Machine for Classification

    Zhifeng Hao;Lifang He;Bingqian Chen;Xiaowei Yang

  • The one-against-all partition based binary tree support vector machine algorithms for multi-class classification

    Xiaowei Yang;Qiaozhen Yu;Lifang He;Tengjiao Guo

  • Multi-VAE: Learning Disentangled View-Common and View-Peculiar Visual Representations for Multi-View Clustering

    Jie Xu;Yazhou Ren;Huayi Tang;Xiaorong Pu

  • Online multi-view clustering with incomplete views

    Weixiang Shao;Lifang He;Chun-ta Lu;Philip S. Yu

  • Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks.

    Jianxin Li;Hao Peng;Yuwei Cao;Yingtong Dou

  • A Survey on Text Classification: From Shallow to Deep Learning

    Qian Li;Hao Peng;Jianxin Li;Congying Xia

  • Joint Community and Structural Hole Spanner Detection via Harmonic Modularity

    Lifang He;Chun-Ta Lu;Jiaqi Ma;Jianping Cao

  • Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

    Hao Peng;Jianxin Li;Yangqiu Song;Renyu Yang

  • Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks.

    Lichao Sun;Congying Xia;Wenpeng Yin;Tingting Liang

  • Citywide traffic congestion estimation with social media

    Senzhang Wang;Lifang He;Leon Stenneth;Philip S. Yu

  • Computing Urban Traffic Congestions by Incorporating Sparse GPS Probe Data and Social Media Data

    Senzhang Wang;Xiaoming Zhang;Jianping Cao;Lifang He

  • DuSK: A Dual Structure-preserving Kernel for Supervised Tensor Learning with Applications to Neuroimages.

    Lifang He;Xiangnan Kong;Philip S. Yu;Ann B. Ragin

  • Multilinear Factorization Machines for Multi-Task Multi-View Learning

    Chun-Ta Lu;Lifang He;Weixiang Shao;Bokai Cao

  • Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification

    Hao Peng;Jianxin Li;Qiran Gong;Yuanxing Ning

Frequent Co-Authors

Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Jianxin Li
Jianxin Li Tianjin Polytechnic University
Senzhang Wang
Senzhang Wang Central South University
Xiaowei Yang
Xiaowei Yang Shanghai Jiao Tong University
Linlin Shen
Linlin Shen Shenzhen University
Jiayu Zhou
Jiayu Zhou Michigan State University
Xiangnan Kong
Xiangnan Kong Worcester Polytechnic Institute
Yazhou Ren
Yazhou Ren University of Electronic Science and Technology of China
Zhoujun Li
Zhoujun Li Beihang University
Zakirul Alam Bhuiyan
Zakirul Alam Bhuiyan Fordham University

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