World's Best Scientists 2026 revealed!

Tong Zhang 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 Tong Zhang 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+

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

Tong Zhang 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 Tong Zhang 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+

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

Overview

Tong Zhang is a researcher affiliated with the University of Illinois at Urbana-Champaign in the United States. Their work primarily focuses on the field of Computer Science, with an emphasis on Computer Vision and Pattern Recognition, Artificial Intelligence, and related subfields.

The research topics covered by Tong Zhang include advanced image and video retrieval techniques, visual attention and saliency detection, topic modeling, natural language processing techniques, advanced vision and imaging, advanced neural network applications, and machine learning and data classification.

The scientist has contributed significantly to the literature, with recent papers including:

  • Optimal Feature Transport for Cross-View Image Geo-Localization, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders, 2020, arXiv (Cornell University)
  • Semi-supervised Active Salient Object Detection, 2021, Pattern Recognition
  • Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment, 2023, arXiv (Cornell University)

Frequent coauthors of Tong Zhang include Sabine Süsstrunk, Yuchao Dai, Mathieu Salzmann, Jipeng Zhang, and Shizhe Diao. These collaborations reflect ongoing work across multiple projects and topics within their research areas.

Tong Zhang has published extensively in several venues, notably:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • SSRN Electronic Journal
  • Pattern Recognition

The concentration of publications in these venues indicates a focus on sharing research findings related to artificial intelligence, pattern recognition, and computer vision for academic and professional audiences.

Best Publications

  • Solving large scale linear prediction problems using stochastic gradient descent algorithms

    Tong Zhang

  • Efficient mini-batch training for stochastic optimization

    Mu Li;Tong Zhang;Yuqiang Chen;Alexander J. Smola

  • The Benefit of Group Sparsity

    Junzhou Huang;Tong Zhang

  • Learning with Structured Sparsity

    Junzhou Huang;Tong Zhang;Dimitris Metaxas

  • Analysis of Multi-stage Convex Relaxation for Sparse Regularization

    Tong Zhang

  • Spatial–Temporal Recurrent Neural Network for Emotion Recognition

    Tong Zhang;Wenming Zheng;Zhen Cui;Yuan Zong

  • Multi-Label Prediction via Compressed Sensing

    John Langford;Tong Zhang;Daniel J. Hsu;Sham M Kakade

  • Sparse Recovery With Orthogonal Matching Pursuit Under RIP

    Tong Zhang

  • UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

    Jing Zhang;Deng-Ping Fan;Yuchao Dai;Saeed Anwar

  • Deep Subspace Clustering Networks

    Pan Ji;Tong Zhang;Hongdong Li;Mathieu Salzmann

  • Involution: Inverting the Inherence of Convolution for Visual Recognition

    Duo Li;Jie Hu;Changhu Wang;Xiangtai Li

  • The Epoch-Greedy algorithm for contextual multi-armed bandits

    John Langford;Tong Zhang

  • Adaptive Sampling Towards Fast Graph Representation Learning

    Wenbing Huang;Tong Zhang;Yu Rong;Junzhou Huang

  • Adaptive Forward-Backward Greedy Algorithm for Learning Sparse Representations

    Tong Zhang

  • A Deep Neural Network-Driven Feature Learning Method for Multi-view Facial Expression Recognition

    Tong Zhang;Wenming Zheng;Zhen Cui;Yuan Zong

  • Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

    Aixuan Li;Jing Zhang;Yunqiu Lv;Bowen Liu

  • Adaptive Forward-Backward Greedy Algorithm for Sparse Learning with Linear Models

    Tong Zhang

  • On the Consistency of Feature Selection using Greedy Least Squares Regression

    Tong Zhang

  • Learning with structured sparsity

    Junzhou Huang;Tong Zhang;Dimitris Metaxas

  • Modeling Localness for Self-Attention Networks

    Baosong Yang;Zhaopeng Tu;Derek F. Wong;Fandong Meng

  • Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

    Jing Zhang;Tong Zhang;Yuchao Daf;Mehrtash Harandi

  • Multi-Head Attention with Disagreement Regularization

    Jian Li;Zhaopeng Tu;Baosong Yang;Michael R. Lyu

  • Design of Highly Nonlinear Substitution Boxes Based on I-Ching Operators

    Tong Zhang;C. L. Philip Chen;Long Chen;Xiangmin Xu

  • Improved Local Coordinate Coding using Local Tangents

    Kai Yu;Tong Zhang

  • Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization

    Jiaxiang Wu;Weidong Huang;Junzhou Huang;Tong Zhang

  • Optimal Feature Transport for Cross-View Image Geo-Localization

    Yujiao Shi;Xin Yu;Liu Liu;Tong Zhang

  • Efficient Optimal Learning for Contextual Bandits

    Miroslav Dudik;Daniel Hsu;Satyen Kale;Nikos Karampatziakis

  • Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization

    Xiaotong Yuan;Xiaotong Yuan;Ping Li;Tong Zhang

  • End-to-End Active Object Tracking and Its Real-World Deployment via Reinforcement Learning

    Wenhan Luo;Peng Sun;Fangwei Zhong;Wei Liu

  • Multi-cue fusion for emotion recognition in the wild

    Jingwei Yan;Wenming Zheng;Zhen Cui;Chuangao Tang

  • A robust risk minimization based named entity recognition system

    Tong Zhang;David Johnson

  • A Novel Neural Network Model based on Cerebral Hemispheric Asymmetry for EEG Emotion Recognition.

    Yang Li;Wenming Zheng;Zhen Cui;Tong Zhang

  • Cross-Corpus Speech Emotion Recognition Based on Domain-Adaptive Least-Squares Regression

    Yuan Zong;Wenming Zheng;Tong Zhang;Xiaohua Huang

  • Exploiting Deep Representations for Neural Machine Translation

    Zi-Yi Dou;Zhaopeng Tu;Xing Wang;Shuming Shi

  • Unsupervised Image-to-Image Translation with Stacked Cycle-Consistent Adversarial Networks

    Minjun Li;Haozhi Huang;Lin Ma;Wei Liu

  • Sparse Online Learning via Truncated Gradient

    John Langford;Lihong Li;Tong Zhang

  • Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

    Jing Zhang;Tong Zhang;Yuchao Dai;Mehrtash Harandi

Frequent Co-Authors

Wenbing Huang
Wenbing Huang Renmin University of China
Hongdong Li
Hongdong Li Australian National University
Yuchao Dai
Yuchao Dai Northwestern Polytechnical University
Mehrtash Harandi
Mehrtash Harandi Monash University
Richard Hartley
Richard Hartley Australian National University
Ian Reid
Ian Reid University of Adelaide
Junzhou Huang
Junzhou Huang The University of Texas at Arlington
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Lars Petersson
Lars Petersson Commonwealth Scientific and Industrial Research Organisation
Fatih Porikli
Fatih Porikli Australian National University

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