World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
10899
World Ranking
6403
National Ranking
2859

Sheng 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 Sheng 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: 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: 362 publications — 83rd percentile

83% of scientists in this discipline score the same or lower.

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

Sheng 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 Sheng Li 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Sheng Li is affiliated with the University of Virginia in the United States and has an extensive publication record across multiple fields, primarily in computer science and engineering. Their research spans artificial intelligence, molecular biology, computer vision and pattern recognition, biomedical engineering, and computational mechanics.

The scientist's main topics of work include:

  • Domain Adaptation and Few-Shot Learning
  • Topic Modeling
  • Adversarial Robustness in Machine Learning
  • Genomics and Phylogenetic Studies
  • Machine Learning in Bioinformatics
  • Advanced Causal Inference Techniques
  • Advanced Graph Neural Networks

Among their recent publications are:

  • A Survey on Causal Inference (2021), published in ACM Transactions on Knowledge Discovery from Data
  • Climate change: Strategies for mitigation and adaptation (2023), published in The Innovation Geoscience
  • AugGPT: Leveraging ChatGPT for Text Data Augmentation (2023), published in arXiv (Cornell University)
  • A high-efficiency and sustainable leaching process of vanadium from shale in sulfuric acid systems enhanced by ultrasound (2020), published in Separation and Purification Technology
  • Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases (2020), published in eLife

Sheng Li frequently collaborates with other researchers, with notable coauthors including:

  • Zhixuan Chu
  • Ronghang Zhu
  • Xin Yin
  • Yu Jiang
  • Lingkai Kong

In terms of publication venues, Sheng Li has contributed most notably to:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Mitochondrial DNA Part B
  • SSRN Electronic Journal
  • IEEE Transactions on Big Data

The scientist has also contributed to book publications, including a title published by Frontiers Media:

  • Leveraging Machine Learning for Omics-driven Biomarker Discovery (2023)

Best Publications

  • McPAT: an integrated power, area, and timing modeling framework for multicore and manycore architectures

    Sheng Li;Jung Ho Ahn;Richard D. Strong;Jay B. Brockman

  • Deep Collaborative Filtering via Marginalized Denoising Auto-encoder

    Sheng Li;Jaya Kawale;Yun Fu

  • Detecting and correcting systematic variation in large-scale RNA sequencing data

    Sheng Li;Paweł P Łabaj;Paul Zumbo;Peter Sykacek

  • A Survey on Causal Inference

    Liuyi Yao;Zhixuan Chu;Sheng Li;Yaliang Li

  • Scene Graph Generation With External Knowledge and Image Reconstruction

    Jiuxiang Gu;Handong Zhao;Zhe Lin;Sheng Li

  • A domain-specific supercomputer for training deep neural networks

    Norman P. Jouppi;Doe Hyun Yoon;George Kurian;Sheng Li

  • Advanced Wearable Microfluidic Sensors for Healthcare Monitoring

    Sheng Li;Zhong Ma;Zhonglin Cao;Lijia Pan

  • ChatAug: Leveraging ChatGPT for Text Data Augmentation

    Unknown

  • Representation Learning for Treatment Effect Estimation from Observational Data

    Liuyi Yao;Sheng Li;Yaliang Li;Mengdi Huai

  • Learning Robust and Discriminative Subspace With Low-Rank Constraints

    Sheng Li;Yun Fu

  • From Ensemble Clustering to Multi-View Clustering.

    Zhiqiang Tao;Hongfu Liu;Sheng Li;Zhengming Ding

  • Fast Spatio-Temporal Residual Network for Video Super-Resolution

    Sheng Li;Fengxiang He;Bo Du;Lefei Zhang

  • Graph Adaptive Knowledge Transfer for Unsupervised Domain Adaptation

    Zhengming Ding;Sheng Li;Ming Shao;Yun Fu

  • Learning low-rank and discriminative dictionary for image classification ☆

    Liangyue Li;Sheng Li;Yun Fu

  • Face Recognition Based on Deep Learning

    Unknown

  • Cross-view projective dictionary learning for person re-identification

    Sheng Li;Ming Shao;Yun Fu

  • Temporal Subspace Clustering for Human Motion Segmentation

    Sheng Li;Kang Li;Yun Fu

  • Faster CNNs with Direct Sparse Convolutions and Guided Pruning

    Jongsoo Park;Sheng Li;Wei Wen;Ping Tak Peter Tang

  • Infinite Ensemble for Image Clustering

    Hongfu Liu;Ming Shao;Sheng Li;Yun Fu

  • Pivot Approach for Extracting Paraphrase Patterns from Bilingual Corpora

    Shiqi Zhao;Haifeng Wang;Ting Liu;Sheng Li

  • Deep evolutionary analysis reveals the design principles of fold A glycosyltransferases.

    Rahil Taujale;Aarya Venkat;Liang-Chin Huang;Zhongliang Zhou

  • Visual to Text: Survey of Image and Video Captioning

    Sheng Li;Zhiqiang Tao;Kang Li;Yun Fu

  • Marginalized Multiview Ensemble Clustering

    Zhiqiang Tao;Hongfu Liu;Sheng Li;Zhengming Ding

  • Co-embedding of Nodes and Edges with Graph Neural Networks.

    Xiaodong Jiang;Ronghang Zhu;Sheng Li;Pengsheng Ji

  • Person Re-Identification by Cross-View Multi-Level Dictionary Learning

    Sheng Li;Ming Shao;Yun Fu

  • Learning Balanced and Unbalanced Graphs via Low-Rank Coding

    Sheng Li;Yun Fu

  • CensNet: Convolution with Edge-Node Switching in Graph Neural Networks.

    Xiaodong Jiang;Pengsheng Ji;Sheng Li

Frequent Co-Authors

Yun Fu
Yun Fu Northeastern University
Xiao-Yuan Jing
Xiao-Yuan Jing Wuhan University
Zhao Zhang
Zhao Zhang Hefei University of Technology
Zhengming Ding
Zhengming Ding Tulane University
Guangcan Liu
Guangcan Liu Southeast University
Yaliang Li
Yaliang Li Alibaba Group (China)
Shuicheng Yan
Shuicheng Yan National University of Singapore
Jingyu Yang
Jingyu Yang Nanjing University of Science and Technology
David Zhang
David Zhang Chinese University of Hong Kong, Shenzhen
Jing Gao
Jing Gao Purdue University West Lafayette

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