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Cho-Jui Hsieh

D-Index & Metrics

Computer Science

D-Index
74
Citations
33250
World Ranking
1457
National Ranking
760

Cho-Jui Hsieh 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 Cho-Jui Hsieh 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: 303 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Cho-Jui Hsieh 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 Cho-Jui Hsieh 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: 74 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Cho-Jui Hsieh is affiliated with the University of California, Los Angeles in the United States and has a research profile primarily focused on computer science with a strong emphasis on artificial intelligence.

Their recent research contributions include the following papers:

  • DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification (2021), published in arXiv (Cornell University)
  • Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples (2020), published in Proceedings of the AAAI Conference on Artificial Intelligence
  • Symbolic Discovery of Optimization Algorithms (2023), published in arXiv (Cornell University)
  • Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations (2020), published in arXiv (Cornell University)
  • When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations (2021), published in arXiv (Cornell University)

Frequent coauthors who have collaborated extensively with Cho-Jui Hsieh include:

  • Pin-Yu Chen
  • Minhao Cheng
  • Inderjit S. Dhillon
  • Zhouxing Shi
  • Ruochen Wang

The scientist's work appears prominently in several publication venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • IEEE Transactions on Neural Networks and Learning Systems
  • Neural Networks

The main field of study is computer science, with key subfields including:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering
  • Computational Mechanics

Cho-Jui Hsieh's research topics focus on several areas related to machine learning and artificial intelligence:

  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications
  • Advanced Neural Network Applications
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Natural Language Processing Techniques

Best Publications

  • LIBLINEAR: A Library for Large Linear Classification

    Rong-En Fan;Kai-Wei Chang;Cho-Jui Hsieh;Xiang-Rui Wang

  • ZOO: Zeroth Order Optimization Based Black-box Attacks to Deep Neural Networks without Training Substitute Models

    Pin-Yu Chen;Huan Zhang;Yash Sharma;Jinfeng Yi

  • VisualBERT: A Simple and Performant Baseline for Vision and Language.

    Liunian Harold Li;Mark Yatskar;Da Yin;Cho-Jui Hsieh

  • A dual coordinate descent method for large-scale linear SVM

    Cho-Jui Hsieh;Kai-Wei Chang;Chih-Jen Lin;S. Sathiya Keerthi

  • Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

    Wei-Lin Chiang;Xuanqing Liu;Si Si;Yang Li

  • Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent

    Xiangru Lian;Ce Zhang;Huan Zhang;Cho-Jui Hsieh

  • Training and Testing Low-degree Polynomial Data Mappings via Linear SVM

    Yin-Wen Chang;Cho-Jui Hsieh;Kai-Wei Chang;Michael Ringgaard

  • EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

    Pin-Yu Chen;Yash Sharma;Huan Zhang;Jinfeng Yi

  • Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

    Yang You;Jing Li;Sashank Reddi;Jonathan Hseu

  • Towards Fast Computation of Certified Robustness for ReLU Networks

    Tsui-Wei Weng;Huan Zhang;Hongge Chen;Zhao Song

  • ImageNet Training in Minutes

    Yang You;Zhao Zhang;Cho-Jui Hsieh;James Demmel

  • Efficient Neural Network Robustness Certification with General Activation Functions

    Huan Zhang;Tsui-Wei Weng;Pin-Yu Chen;Cho-Jui Hsieh

  • Towards Robust Neural Networks via Random Self-ensemble

    Xuanqing Liu;Minhao Cheng;Huan Zhang;Cho-Jui Hsieh

  • Large Linear Classification When Data Cannot Fit in Memory

    Hsiang-Fu Yu;Cho-Jui Hsieh;Kai-Wei Chang;Chih-Jen Lin

  • Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation

    Cho-jui Hsieh;Inderjit S. Dhillon;Pradeep K. Ravikumar;Mátyás A. Sustik

  • AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks

    Chun-Chen Tu;Paishun Ting;Pin-Yu Chen;Sijia Liu

  • Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems

    Hsiang-Fu Yu;Cho-Jui Hsieh;Si Si;Inderjit Dhillon

  • Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines

    Kai-Wei Chang;Cho-Jui Hsieh;Chih-Jen Lin

  • Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

    Tsui-Wei Weng;Huan Zhang;Pin-Yu Chen;Jinfeng Yi

  • Memory efficient kernel approximation

    Si Si;Cho-Jui Hsieh;Inderjit S. Dhillon

  • Towards Stable and Efficient Training of Verifiably Robust Neural Networks

    Huan Zhang;Hongge Chen;Chaowei Xiao;Sven Gowal

Frequent Co-Authors

Huan Zhang
Huan Zhang University of California, Los Angeles
Inderjit S. Dhillon
Inderjit S. Dhillon Google (United States)
Jinfeng Yi
Jinfeng Yi IBM (United States)
Pin-Yu Chen
Pin-Yu Chen IBM (United States)
Kai-Wei Chang
Kai-Wei Chang University of California, Los Angeles
Duane S. Boning
Duane S. Boning MIT
Sanjiv Kumar
Sanjiv Kumar Google (United States)
James Demmel
James Demmel University of California, Berkeley
Yang You
Yang You National University of Singapore
Pradeep Ravikumar
Pradeep Ravikumar Carnegie Mellon University

External Links

Personal website of Cho-Jui Hsieh Google Scholar page

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Best Scientists Citing Cho-Jui Hsieh

Pin-Yu Chen

Pin-Yu Chen

IBM (United States)

Publications: 54

Ivor W. Tsang

Ivor W. Tsang

Agency for Science, Technology and Research

Publications: 45

Chih-Jen Lin

Chih-Jen Lin

National Taiwan University

Publications: 38

Dacheng Tao

Dacheng Tao

Nanyang Technological University

Publications: 36

Björn Schuller

Björn Schuller

Imperial College London

Publications: 35

Jiliang Tang

Jiliang Tang

Michigan State University

Publications: 35

Sijia Liu

Sijia Liu

Michigan State University

Publications: 34

Inderjit S. Dhillon

Inderjit S. Dhillon

Google (United States)

Publications: 33

Qi Tian

Qi Tian

Huawei Technologies (China)

Publications: 33

Peter Richtárik

Peter Richtárik

King Abdullah University of Science and Technology

Publications: 32

Zhi-Hua Zhou

Zhi-Hua Zhou

Nanjing University

Publications: 28

Huan Liu

Huan Liu

Arizona State University

Publications: 28

Tong Zhang

Tong Zhang

University of Illinois at Urbana-Champaign

Publications: 27

Ping Li

Ping Li

Baidu (China)

Publications: 27

Wotao Yin

Wotao Yin

Alibaba Group (China)

Publications: 27

Eric P. Xing

Eric P. Xing

Mohamed bin Zayed University of Artificial Intelligence

Publications: 26

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