World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
7769
World Ranking
11490
National Ranking
1424

Xiuqiang 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 Xiuqiang 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: 151 publications — 27th percentile

27% of scientists in this discipline score the same or lower.

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

Xiuqiang 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 Xiuqiang 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

Xiuqiang He is affiliated with Huawei Technologies in China and has contributed extensively to research in computer science with a focus on artificial intelligence and information systems. They have published 193 works mainly in the field of computer science, with specific contributions spanning artificial intelligence, information systems, computer vision and pattern recognition, management science and operations research, and computer networks and communications.

Their research interests include several prominent topics, notably recommender systems and techniques, advanced graph neural networks, topic modeling, advanced bandit algorithms research, domain adaptation and few-shot learning, caching and content delivery, and machine learning and data classification.

Frequent coauthors of Xiuqiang He include Ruiming Tang, Dugang Liu, Xing Tang, Zhenhua Dong, and Weinan Zhang, indicating ongoing collaboration within a network of researchers with complementary expertise.

The venues where Xiuqiang He has most often published include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Information Systems
  • Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • IEEE Transactions on Knowledge and Data Engineering

Significant recent publications by Xiuqiang He include:

  • "Graph Heterogeneous Multi-Relational Recommendation," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "State representation modeling for deep reinforcement learning based recommendation," 2020, Knowledge-Based Systems
  • "Improving Knowledge Tracing with Collaborative Information," 2022, Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • "Less Is Better: Unweighted Data Subsampling via Influence Function," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction," 2020, arXiv (Cornell University)

Best Publications

  • DeepFM: a factorization-machine based neural network for CTR prediction

    Huifeng Guo;Ruiming Tang;Yunming Ye;Zhenguo Li

  • DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

    Huifeng Guo;Ruiming Tang;Yunming Ye;Zhenguo Li

  • UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation

    Kelong Mao;Jieming Zhu;Xi Xiao;Biao Lu

  • Federated Meta-Learning with Fast Convergence and Efficient Communication

    Fei Chen;Mi Luo;Zhenhua Dong;Zhenguo Li

  • Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data

    Yanru Qu;Bohui Fang;Weinan Zhang;Ruiming Tang

  • AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

    Bin Liu;Chenxu Zhu;Guilin Li;Weinan Zhang

  • A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data

    Dugang Liu;Pengxiang Cheng;Zhenhua Dong;Xiuqiang He

  • Graph Heterogeneous Multi-Relational Recommendation

    Chong Chen;Weizhi Ma;Min Zhang;Zhaowei Wang

  • Transient Stability Analysis and Enhancement of Renewable Energy Conversion System During LVRT

    Xiuqiang He;Hua Geng;Ruiqi Li;Bikash Chandra Pal

  • Neighbor Interaction Aware Graph Convolution Networks for Recommendation

    Jianing Sun;Yingxue Zhang;Wei Guo;Huifeng Guo

  • Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

    Sijin Zhou;Xinyi Dai;Haokun Chen;Weinan Zhang

  • SimpleX: A Simple and Strong Baseline for Collaborative Filtering

    Kelong Mao;Jieming Zhu;Jinpeng Wang;Quanyu Dai

  • Multi-graph Convolution Collaborative Filtering

    Jianing Sun;Yingxue Zhang;Chen Ma;Mark Coates

  • Federated Meta-Learning for Recommendation

    Fei Chen;Zhenhua Dong;Zhenguo Li;Xiuqiang He

  • Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding

    Zhu Zhang;Zhou Zhao;Zhijie Lin;jieming zhu

  • Open Benchmarking for Click-Through Rate Prediction

    Jieming Zhu;Jinyang Liu;Shuai Yang;Qi Zhang

  • Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos

    Zhu Zhang;Zhijie Lin;Zhou Zhao;Jieming Zhu

  • UNBERT: User-News Matching BERT for News Recommendation.

    Qi Zhang;Jingjie Li;Qinglin Jia;Chuyuan Wang

  • A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks

    Jianing Sun;Wei Guo;Dengcheng Zhang;Yingxue Zhang

  • Deep Learning for Click-Through Rate Estimation

    Weinan Zhang;Jiarui Qin;Wei Guo;Ruiming Tang

  • Mitigating Confounding Bias in Recommendation via Information Bottleneck

    Dugang Liu;Pengxiang Cheng;Hong Zhu;Zhenhua Dong

  • A Generalized Design Framework of Notch Filter Based Frequency-Locked Loop for Three-Phase Grid Voltage

    Xiuqiang He;Hua Geng;Geng Yang

Frequent Co-Authors

Weinan Zhang
Weinan Zhang Shanghai Jiao Tong University
Hua Geng
Hua Geng Tsinghua University
Zhenguo Li
Zhenguo Li Huawei Technologies (China)
Yong Yu
Yong Yu Shanghai Jiao Tong University
Yunming Ye
Yunming Ye Harbin Institute of Technology
Zonghua Gu
Zonghua Gu Hofstra University
Zhou Zhao
Zhou Zhao Zhejiang University
Geng Yang
Geng Yang Tsinghua University
Jun Wang
Jun Wang University College London
Mark Coates
Mark Coates McGill University

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