World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
62
Citations
16956
World Ranking
2879
National Ranking
394

Hongyu 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 Hongyu 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+

This scientist: 516 publications — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Hongyu 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 Hongyu 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+

This scientist: 62 D-Index — 80th percentile

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

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

Research.com Recognitions

  • 2020 - ACM Distinguished Member

Overview

Hongyu Zhang is affiliated with Chongqing University in China and has a substantial body of research primarily within the field of Computer Science. Their work encompasses several subfields including Artificial Intelligence, Information Systems, Computer Networks and Communications, Electrical and Electronic Engineering, and Software.

The scientist's research topics reflect a strong focus on Software Engineering Research, with significant contributions to Software System Performance and Reliability. Other key topics they explore include Topic Modeling, Software Testing and Debugging Techniques, Natural Language Processing Techniques, Software Reliability and Analysis Research, and Advanced Malware Detection Techniques.

Hongyu Zhang has published extensively in various academic venues. The most frequent outlets for their work are:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • ACM Transactions on Software Engineering and Methodology
  • Proceedings of the 44th International Conference on Software Engineering
  • Automated Software Engineering

They have collaborated regularly with several coauthors, including Yanlin Wang, Dongmei Zhang, Yao Wan, Lun Du, and Ensheng Shi, with collaboration counts ranging from 16 to 30 joint works.

Among recent publications of note are the following papers:

  • "General synthesis of ultrafine metal oxide/reduced graphene oxide nanocomposites for ultrahigh-flux nanofiltration membrane," 2022, Nature Communications
  • "Log-based Anomaly Detection Without Log Parsing," 2021, 2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)
  • "A Survey of Compiler Testing," 2020, ACM Computing Surveys
  • "A parallel GRU with dual-stage attention mechanism model integrating uncertainty quantification for probabilistic RUL prediction of wind turbine bearings," 2023, Reliability Engineering & System Safety
  • "UniParser: A Unified Log Parser for Heterogeneous Log Data," 2022, Proceedings of the ACM Web Conference 2022

Hongyu Zhang has received recognition such as the ACM Distinguished Member award in 2020.

Best Publications

  • A novel neural source code representation based on abstract syntax tree

    Jian Zhang;Xu Wang;Hongyu Zhang;Hailong Sun

  • Where should the bugs be fixed? - more accurate information retrieval-based bug localization based on bug reports

    Jian Zhou;Hongyu Zhang;David Lo

  • Robust log-based anomaly detection on unstable log data

    Xu Zhang;Yong Xu;Qingwei Lin;Bo Qiao

  • Deep API learning

    Xiaodong Gu;Hongyu Zhang;Dongmei Zhang;Sunghun Kim

  • Deep code search

    Xiaodong Gu;Hongyu Zhang;Sunghun Kim

  • ReLink: recovering links between bugs and changes

    Rongxin Wu;Hongyu Zhang;Sunghun Kim;Shing-Chi Cheung

  • Log clustering based problem identification for online service systems

    Qingwei Lin;Hongyu Zhang;Jian-Guang Lou;Yu Zhang

  • Where should the bugs be fixed? More accurate information retrieval-based bug localization based on bug reports

    Unknown

  • Dealing with noise in defect prediction

    Sunghun Kim;Hongyu Zhang;Rongxin Wu;Liang Gong

  • Shaping program repair space with existing patches and similar code

    Jiajun Jiang;Yingfei Xiong;Hongyu Zhang;Qing Gao

  • CEO humility, narcissism and firm innovation: A paradox perspective on CEO traits ☆ ☆☆ ★

    Hongyu Zhang;Amy Y. Ou;Anne S. Tsui;Hui Wang

  • Log-based Anomaly Detection Without Log Parsing

    Unknown

  • CodeHow: Effective Code Search Based on API Understanding and Extended Boolean Model (E)

    Fei Lv;Hongyu Zhang;Jian-guang Lou;Shaowei Wang

  • Boosting Bug-Report-Oriented Fault Localization with Segmentation and Stack-Trace Analysis

    Chu-Pan Wong;Yingfei Xiong;Hongyu Zhang;Dan Hao

  • Multi-Criteria Decision-Making Method Based on Distance Measure and Choquet Integral for Linguistic Z-Numbers

    Jian-qiang Wang;Yong-xi Cao;Hong-yu Zhang

  • Retrieval-based neural source code summarization

    Jian Zhang;Xu Wang;Hongyu Zhang;Hailong Sun

  • Sample-based software defect prediction with active and semi-supervised learning

    Ming Li;Hongyu Zhang;Rongxin Wu;Zhi-Hua Zhou

  • Mining succinct and high-coverage API usage patterns from source code

    Jue Wang;Yingnong Dang;Hongyu Zhang;Kai Chen

  • Formal semantics and verification for feature modeling

    Jing Sun;Hongyu Zhang;Yuan Fang;Li Hai Wang

  • An investigation of the relationships between lines of code and defects

    Hongyu Zhang

  • Predicting bug-fixing time: an empirical study of commercial software projects

    Hongyu Zhang;Liang Gong;Steve Versteeg

  • Learning to log: helping developers make informed logging decisions

    Jieming Zhu;Pinjia He;Qiang Fu;Hongyu Zhang

  • Verifying feature models using OWL

    Hai H. Wang;Yuan Fang Li;Jing Sun;Hongyu Zhang

Frequent Co-Authors

Dongmei Zhang
Dongmei Zhang Microsoft (United States)
Qingwei Lin
Qingwei Lin Microsoft (United States)
Dan Hao
Dan Hao Peking University
Jian-Guang Lou
Jian-Guang Lou Microsoft (United States)
Sunghun Kim
Sunghun Kim Hong Kong University of Science and Technology
Lu Zhang
Lu Zhang Peking University
Yingfei Xiong
Yingfei Xiong Peking University
Xiao-Yuan Jing
Xiao-Yuan Jing Wuhan University
Shing-Chi Cheung
Shing-Chi Cheung Hong Kong University of Science and Technology
Michele Marchesi
Michele Marchesi University of Cagliari

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