World's Best Scientists 2026 revealed!
Chaochao Chen

Chaochao Chen

Chaochao Chen 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 Chaochao Chen 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.

Chaochao Chen 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 Chaochao Chen 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

Chaochao Chen is affiliated with Zhejiang University in China and specializes in the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Molecular Biology. The scientist's research is notably concentrated on topics related to Recommender Systems and Techniques, Privacy-Preserving Technologies in Data, Advanced Graph Neural Networks, Stochastic Gradient Optimization Techniques, Topic Modeling, Advanced Bandit Algorithms Research, and Cryptography and Data Security.

They have published extensively in a variety of venues, including:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Knowledge and Data Engineering
  • ACM Transactions on Information Systems
  • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Among recent papers, the following are highlighted:

  • "Differential Private Knowledge Transfer for Privacy-Preserving Cross-Domain Recommendation," 2022, Proceedings of the ACM Web Conference 2022
  • "ASFGNN: Automated separated-federated graph neural network," 2021, Peer-to-Peer Networking and Applications
  • "A Unified Framework for Cross-Domain and Cross-System Recommendations," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "Practical Privacy Preserving POI Recommendation," 2020, ACM Transactions on Intelligent Systems and Technology
  • "Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification," 2022, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Frequent co-authors include:

  • Xiaolin Zheng
  • Weiming Liu
  • Yuyuan Li
  • Jun Zhou

Chaochao Chen's work spans topics deeply embedded in privacy-preserving methods and graph neural networks, with a notable presence in cross-domain recommendation systems that address both theoretical and applied challenges in knowledge transfer and privacy. The collaboration with multiple researchers across AI and data engineering venues reflects a broad engagement with the computer science community, particularly in areas intersecting privacy and advanced neural network architectures.

Best Publications

  • Heterogeneous Graph Neural Networks for Malicious Account Detection

    Ziqi Liu;Chaochao Chen;Xinxing Yang;Jun Zhou

  • GeniePath: Graph Neural Networks with Adaptive Receptive Paths

    Ziqi Liu;Chaochao Chen;Longfei Li;Jun Zhou

  • Cross-Domain Recommendation: Challenges, Progress, and Prospects

    Feng Zhu;Yan Wang;Chaochao Chen;Jun Zhou

  • DTCDR: A Framework for Dual-Target Cross-Domain Recommendation

    Feng Zhu;Chaochao Chen;Yan Wang;Guanfeng Liu

  • A graphical and attentional framework for dual-target cross-domain recommendation

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • A Deep Framework for Cross-Domain and Cross-System Recommendations.

    Feng Zhu;Yan Wang;Chaochao Chen;Guanfeng Liu

  • A hybrid approach for movie recommendation via tags and ratings

    Shouxian Wei;Xiaolin Zheng;Deren Chen;Chaochao Chen

  • Context- ware collaborative topic regression with social matrix factorization for recommender systems

    Chaochao Chen;Xiaolin Zheng;Yan Wang;Fuxing Hong

  • Towards Context-aware Social Recommendation via Individual Trust

    Jun Li;Chaochao Chen;Huiling Chen;Changfei Tong

  • When Homomorphic Encryption Marries Secret Sharing: Secure Large-Scale Sparse Logistic Regression and Applications in Risk Control

    Chaochao Chen;Jun Zhou;Li Wang;Xibin Wu

  • A Unified Framework for Cross-Domain and Cross-System Recommendations

    Feng Zhu;Yan Wang;Jun Zhou;Chaochao Chen

  • FinBrain: when finance meets AI 2.0

    Xiao-lin Zheng;Meng-ying Zhu;Qi-bing Li;Chao-chao Chen

  • ASFGNN: Automated separated-federated graph neural network

    Longfei Zheng;Jun Zhou;Chaochao Chen;Bingzhe Wu

  • Distributed Deep Forest and its Application to Automatic Detection of Cash-Out Fraud

    Ya-Lin Zhang;Jun Zhou;Wenhao Zheng;Ji Feng

  • Practical Privacy Preserving POI Recommendation

    Chaochao Chen;Jun Zhou;Bingzhe Wu;Wenjing Fang

  • Privacy Preserving Point-of-Interest Recommendation Using Decentralized Matrix Factorization

    Chaochao Chen;Ziqi Liu;Peilin Zhao;Jun Zhou

  • A Hybrid Trust-Based Recommender System for Online Communities of Practice

    Xiao-Lin Zheng;Chao-Chao Chen;Jui-Long Hung;Wu He

  • KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial

    Jun Zhou;Xiaolong Li;Peilin Zhao;Chaochao Chen

  • Privacy-Preserving Graph Neural Network for Node Classification.

    Jun Zhou;Chaochao Chen;Longfei Zheng;Xiaolin Zheng

  • Distributed Deep Forest and its Application to Automatic Detection of Cash-out Fraud

    Ya-Lin Zhang;Jun Zhou;Wenhao Zheng;Ji Feng

Frequent Co-Authors

Yan Wang
Yan Wang Macquarie University
Guanfeng Liu
Guanfeng Liu Macquarie University
Peilin Zhao
Peilin Zhao Tencent (China)
Le Song
Le Song Mohamed bin Zayed University of Artificial Intelligence
Alex X. Liu
Alex X. Liu Michigan State University
Guangyu Sun
Guangyu Sun Peking University
Jia Wu
Jia Wu Macquarie University
Zhi-Hua Zhou
Zhi-Hua Zhou Nanjing University
Kevin Chen-Chuan Chang
Kevin Chen-Chuan Chang University of Illinois at Urbana-Champaign
Wu He
Wu He Old Dominion University

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