World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
78
Citations
23032
World Ranking
1208
National Ranking
167

Xueqi Cheng 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 Xueqi Cheng 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: 583 publications — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Xueqi Cheng 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 Xueqi Cheng 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: 78 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

Overview

Xueqi Cheng is affiliated with the Chinese Academy of Sciences in China and has contributed extensively to the field of Computer Science. Their research spans across several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics, and Management Science and Operations Research.

The scientist's work covers a wide range of topics such as:

  • Topic Modeling
  • Advanced Graph Neural Networks
  • Natural Language Processing Techniques
  • Domain Adaptation and Few-Shot Learning
  • Complex Network Analysis Techniques
  • Multimodal Machine Learning Applications
  • Adversarial Robustness in Machine Learning

Among their recent papers are:

  • "FlowScope: Spotting Money Laundering Based on Graphs," 2020, published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Semantic Models for the First-Stage Retrieval: A Comprehensive Review," 2022, published in ACM Transactions on Information Systems
  • "Combating emerging financial risks in the big data era: A perspective review," 2021, published in Fundamental Research
  • "Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis," 2024, published in IEEE Transactions on Knowledge and Data Engineering
  • "Time Series Anomaly Detection With Adversarial Reconstruction Networks," 2022, published in IEEE Transactions on Knowledge and Data Engineering

Xueqi Cheng frequently collaborates with the following co-authors:

  • Jiafeng Guo
  • Huawei Shen
  • Ruqing Zhang
  • Yixing Fan
  • Liang Pang

Publications by the scientist appear frequently in the following venues:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Information Systems
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Best Publications

  • A biterm topic model for short texts

    Xiaohui Yan;Jiafeng Guo;Yanyan Lan;Xueqi Cheng

  • Significance and Challenges of Big Data Research

    Xiaolong Jin;Benjamin W. Wah;Xueqi Cheng;Yuanzhuo Wang

  • Detect overlapping and hierarchical community structure in networks

    Huawei Shen;Xueqi Cheng;Kai Cai;Mao-Bin Hu

  • A survey on sentiment detection of reviews

    Huifeng Tang;Songbo Tan;Xueqi Cheng

  • BTM: Topic Modeling over Short Texts

    Xueqi Cheng;Xiaohui Yan;Yanyan Lan;Jiafeng Guo

  • Text matching as image recognition

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Named entity recognition in query

    Jiafeng Guo;Gu Xu;Xueqi Cheng;Hang Li

  • Learning Hierarchical Representation Model for NextBasket Recommendation

    Pengfei Wang;Jiafeng Guo;Yanyan Lan;Jun Xu

  • Cross-domain recommendation: an embedding and mapping approach

    Tong Man;Huawei Shen;Xiaolong Jin;Xueqi Cheng

  • A Deep Look into neural ranking models for information retrieval

    Jiafeng Guo;Yixing Fan;Liang Pang;Liu Yang

  • A deep architecture for semantic matching with multiple positional sentence representations

    Shengxian Wan;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Adapting Naive Bayes to Domain Adaptation for Sentiment Analysis

    Songbo Tan;Xueqi Cheng;Yuefen Wang;Hongbo Xu

  • DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval

    Liang Pang;Yanyan Lan;Jiafeng Guo;Jun Xu

  • Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning

    Zixuan Li;Xiaolong Jin;Wei Li;Saiping Guan

  • BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series

    Bin Zhou;Shenghua Liu;Bryan Hooi;Xueqi Cheng

  • DeepHawkes: Bridging the Gap between Prediction and Understanding of Information Cascades

    Qi Cao;Huawei Shen;Keting Cen;Wentao Ouyang

  • Predict anchor links across social networks via an embedding approach

    Tong Man;Huawei Shen;Shenghua Liu;Xiaolong Jin

  • Survey and taxonomy of feature selection algorithms in intrusion detection system

    You Chen;Yang Li;Xue-Qi Cheng;Li Guo

  • StaticGreedy: solving the scalability-accuracy dilemma in influence maximization

    Suqi Cheng;Huawei Shen;Junming Huang;Guoqing Zhang

  • Graph Wavelet Neural Network.

    Bingbing Xu;Huawei Shen;Qi Cao;Yunqi Qiu

  • Chinese Lexical Analysis Using Hierarchical Hidden Markov Model

    Hua-Ping Zhang;Qun Liu;Xue-Qi Cheng;Hao Zhang

  • Proceedings of the Eighth ACM International Conference on Web Search and Data Mining

    Xueqi Cheng;Hang Li;Evgeniy Gabrilovich;Jie Tang

Frequent Co-Authors

Jiafeng Guo
Jiafeng Guo Chinese Academy of Sciences
Yanyan Lan
Yanyan Lan Chinese Academy of Sciences
Huawei Shen
Huawei Shen Chinese Academy of Sciences
Jun Xu
Jun Xu Renmin University of China
Kun Yang
Kun Yang University of Essex
Fei Sun
Fei Sun Institute Of Computing Technology
Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Tao Zhou
Tao Zhou University of Electronic Science and Technology of China
Tao Qin
Tao Qin Microsoft (United States)
Mao-Bin Hu
Mao-Bin Hu University of Science and Technology of China

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