World's Best Scientists 2026 revealed!
Xi-Zhao Wang

Xi-Zhao Wang

D-Index & Metrics

Computer Science

D-Index
63
Citations
13750
World Ranking
2790
National Ranking
379

Xi-Zhao Wang 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 Xi-Zhao Wang 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: 339 publications — 80th percentile

80% of scientists in this discipline score the same or lower.

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

Xi-Zhao Wang 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 Xi-Zhao Wang 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: 63 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

Xi-Zhao Wang is affiliated with Tsinghua University in China and has contributed extensively to the fields of computer science and engineering. Their research spans multiple subfields, including artificial intelligence, computer vision and pattern recognition, computational theory and mathematics, molecular biology, and civil and structural engineering.

Their publication record reflects a focus on several main topics, notably domain adaptation and few-shot learning, machine learning and extreme learning machines (ELM), rough sets and fuzzy logic, imbalanced data classification techniques, neural networks and applications, face and expression recognition, and anomaly detection techniques and applications.

Frequent co-authors in Wang's research include Ran Wang, Xinlei Zhou, Farhad Pourpanah, Weipeng Cao, and Zhiyong Wu.

Some of the recent papers authored or co-authored by Xi-Zhao Wang are:

  • "A Review of Generalized Zero-Shot Learning Methods" (2022), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Recent advances in deep learning" (2020), published in International Journal of Machine Learning and Cybernetics
  • "A broad review on class imbalance learning techniques" (2023), published in Applied Soft Computing
  • "A review of artificial fish swarm algorithms: recent advances and applications" (2022), published in Artificial Intelligence Review
  • "Interval Dominance-Based Feature Selection for Interval-Valued Ordered Data" (2022), published in IEEE Transactions on Neural Networks and Learning Systems

Wang's work has been published frequently in venues such as Information Sciences, SSRN Electronic Journal, Neurocomputing, Knowledge-Based Systems, and arXiv (Cornell University), illustrating a broad engagement across reputable journals and preprint archives.

Best Publications

  • The parameterization reduction of soft sets and its applications

    Degang Chen;E. C. C. Tsang;Daniel S. Yeung;Xizhao Wang

  • Fuzziness based semi-supervised learning approach for intrusion detection system

    Rana Aamir Raza Ashfaq;Xi-Zhao Wang;Joshua Zhexue Huang;Haider Abbas

  • On the generalization of fuzzy rough sets

    D.S. Yeung;Degang Chen;E.C.C. Tsang;J.W.T. Lee

  • A review on neural networks with random weights

    Weipeng Cao;Xizhao Wang;Zhong Ming;Jinzhu Gao

  • Improving fuzzy c -means clustering based on feature-weight learning

    Xizhao Wang;Yadong Wang;Lijuan Wang

  • Attributes Reduction Using Fuzzy Rough Sets

    E.C.C. Tsang;Degang Chen;D.S. Yeung;Xi-Zhao Wang

  • Recent advances in deep learning

    Xizhao Wang;Yanxia Zhao;Farhad Pourpanah

  • A Study on Relationship Between Generalization Abilities and Fuzziness of Base Classifiers in Ensemble Learning

    Xi-Zhao Wang;Hong-Jie Xing;Yan Li;Qiang Hua

  • Feature Selection Based on Neighborhood Discrimination Index

    Changzhong Wang;Qinghua Hu;Xizhao Wang;Degang Chen

  • Learning fuzzy rules from fuzzy samples based on rough set technique

    Xizhao Wang;Eric C. C. Tsang;Suyun Zhao;Degang Chen

  • Improving Generalization of Fuzzy IF--THEN Rules by Maximizing Fuzzy Entropy

    Xi-Zhao Wang;Chun-Ru Dong

  • Localized Generalization Error Model and Its Application to Architecture Selection for Radial Basis Function Neural Network

    D.S. Yeung;W.W.Y. Ng;Defeng Wang;E.C.C. Tsang

  • On the optimization of fuzzy decision trees

    Xizhao Wang;Bin Chen;Guoliang Qian;Feng Ye

  • A comparative study on heuristic algorithms for generating fuzzy decision trees

    X.-Z. Wang;D.S. Yeung;E.C.C. Tsang

  • Maximum Ambiguity-Based Sample Selection in Fuzzy Decision Tree Induction

    Xi-Zhao Wang;Ling-Cai Dong;Jian-Hui Yan

  • Induction of multiple fuzzy decision trees based on rough set technique

    Xi-Zhao Wang;Jun-Hai Zhai;Shu-Xia Lu

  • Joint Optimization of Energy Consumption and Latency in Mobile Edge Computing for Internet of Things

    Laizhong Cui;Chong Xu;Shu Yang;Joshua Zhexue Huang

  • Fuzziness based sample categorization for classifier performance improvement

    Xi-Zhao Wang;Rana Aamir Raza Ashfaq;Ai-Min Fu

  • Intuitionistic Fuzzy Twin Support Vector Machines

    Salim Rezvani;Xizhao Wang;Farhad Pourpanah

  • Upper integral network with extreme learning mechanism

    Xizhao Wang;Aixia Chen;Huimin Feng

  • OWA operator based link prediction ensemble for social network

    Yu-lin He;James N.K. Liu;Yan-xing Hu;Xi-zhao Wang

  • A Review of Generalized Zero-Shot Learning Methods.

    Farhad Pourpanah;Moloud Abdar;Yuxuan Luo;Xinlei Zhou

Frequent Co-Authors

Degang Chen
Degang Chen North China Electric Power University
Joshua Zhexue Huang
Joshua Zhexue Huang Shenzhen University
Witold Pedrycz
Witold Pedrycz University of Alberta
Sam Kwong
Sam Kwong Lingnan University
Laizhong Cui
Laizhong Cui Shenzhen University
Chee Peng Lim
Chee Peng Lim Swinburne University of Technology
Haoran Xie
Haoran Xie Lingnan University
Jianqiang Li
Jianqiang Li Beijing University of Technology
Wei-Zhi Wu
Wei-Zhi Wu Zhejiang Ocean University
Loi Lei Lai
Loi Lei Lai Guangdong University of Technology

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