World's Best Scientists 2026 revealed!
Zhen Ming Jiang

Zhen Ming Jiang

D-Index & Metrics

Computer Science

D-Index
38
Citations
4278
World Ranking
10413
National Ranking
417

Zhen Ming Jiang 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 Zhen Ming Jiang 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: 81 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Zhen Ming Jiang 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 Zhen Ming Jiang 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: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

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

Overview

Zhen Ming Jiang is a researcher affiliated with York University in Canada, focusing primarily on the field of Computer Science with a notable contribution of 52 publications. Their expertise spans several subfields including Information Systems, Artificial Intelligence, Computer Networks and Communications, Software, and Management Information Systems.

Their research covers a range of topics such as Software Engineering Research, Blockchain Technology Applications and Security, Software System Performance and Reliability, Cloud Computing and Resource Management, Data Stream Mining Techniques, Software Reliability and Analysis Research, and Adversarial Robustness in Machine Learning.

Zhen Ming Jiang has authored or co-authored notable papers, including:

  • GitHub Copilot AI pair programmer: Asset or Liability? (2023) published in Journal of Systems and Software
  • An exploratory study of smart contracts in the Ethereum blockchain platform (2020) published in Empirical Software Engineering
  • Developing Cost-Effective Blockchain-Powered Applications (2021) published in ACM Transactions on Software Engineering and Methodology
  • Predicting Node Failures in an Ultra-Large-Scale Cloud Computing Platform (2020) published in ACM Transactions on Software Engineering and Methodology
  • Keeping Deep Learning Models in Check: A History-Based Approach to Mitigate Overfitting (2024) published in IEEE Access

The frequent venues for their publications include:

  • ACM Transactions on Software Engineering and Methodology (7 publications)
  • Empirical Software Engineering (5 publications)
  • ACM Computing Surveys (2 publications)
  • arXiv (Cornell University) (2 publications)
  • Zenodo (CERN European Organization for Nuclear Research) (2 publications)

Collaborations are a key feature of their work, with frequent co-authorship alongside researchers such as Ahmed E. Hassan, Nima Shiri Harzevili, Alvine Boaye Belle, Junjie Wang, and Boyuan Chen.

The scope of Jiang's work integrates theoretical and applied aspects of software engineering and blockchain technology, contributing to understanding software system reliability, performance, and the integration of emerging technologies like AI and blockchain in practical contexts.

Best Publications

  • A Survey on Load Testing of Large-Scale Software Systems

    Zhen Ming Jiang;Ahmed E. Hassan

  • An exploratory study of smart contracts in the Ethereum blockchain platform

    Gustavo Ansaldi Oliva;Ahmed E. Hassan;Zhen Ming (Jack) Jiang

  • Assisting developers of big data analytics applications when deploying on hadoop clouds

    Weiyi Shang;Zhen Ming Jiang;Hadi Hemmati;Brain Adams

  • An exploratory study of the evolution of communicated information about the execution of large software systems

    Weiyi Shang;Zhen Ming Jiang;Bram Adams;Ahmed E. Hassan

  • Detecting performance anti-patterns for applications developed using object-relational mapping

    Tse-Hsun Chen;Weiyi Shang;Zhen Ming Jiang;Ahmed E. Hassan

  • An industrial study on the risk of software changes

    Emad Shihab;Ahmed E. Hassan;Bram Adams;Zhen Ming Jiang

  • Automated performance analysis of load tests

    Zhen Ming Jiang;Ahmed E. Hassan;Gilbert Hamann;Parminder Flora

  • Automatic identification of load testing problems

    Zhen Ming Jiang;A.E. Hassan;G. Hamann;P. Flora

  • Understanding the impact of code and process metrics on post-release defects: a case study on the Eclipse project

    Emad Shihab;Zhen Ming Jiang;Walid M. Ibrahim;Bram Adams

  • GitHub Copilot AI pair programmer: Asset or Liability?

    Unknown

  • Characterizing logging practices in Java-based open source software projects --- a replication study in Apache Software Foundation

    Boyuan Chen;Zhen Ming (Jack) Jiang

  • Mining Performance Regression Testing Repositories for Automated Performance Analysis

    King Chun Foo;Zhen Ming Jiang;Bram Adams;Ahmed E. Hassan

  • Abstracting Execution Logs to Execution Events for Enterprise Applications (Short Paper)

    Zhen Ming Jiang;A.E. Hassan;P. Flora;G. Hamann

  • Automated detection of performance regressions using statistical process control techniques

    Thanh H.D. Nguyen;Bram Adams;Zhen Ming Jiang;Ahmed E. Hassan

  • An automated approach for abstracting execution logs to execution events

    Zhen Ming Jiang;Ahmed E. Hassan;Gilbert Hamann;Parminder Flora

  • Characterizing and detecting anti-patterns in the logging code

    Boyuan Chen;Zhen Ming (Jack) Jiang

  • Examining the evolution of code comments in PostgreSQL

    Zhen Ming Jiang;Ahmed E. Hassan

  • Developing Cost-Effective Blockchain-Powered Applications: A Case Study of the Gas Usage of Smart Contract Transactions in the Ethereum Blockchain Platform

    Abdullah A. Zarir;Gustavo A. Oliva;Zhen M. (Jack) Jiang;Ahmed E. Hassan

  • Automated analysis of load testing results

    Zhen Ming Jiang

  • Predicting Node Failures in an Ultra-Large-Scale Cloud Computing Platform: An AIOps Solution

    Yangguang Li;Zhen Ming (Jack) Jiang;Heng Li;Ahmed E. Hassan

  • A Framework for Studying Clones In Large Software Systems

    Zhen Ming Jiang;A.E. Hassan

  • Identifying crosscutting concerns using historical code changes

    Bram Adams;Zhen Ming Jiang;Ahmed E. Hassan

  • MapReduce as a general framework to support research in Mining Software Repositories (MSR)

    Weiyi Shang;Zhen Ming Jiang;Bram Adams;Ahmed E. Hassan

Frequent Co-Authors

Ahmed E. Hassan
Ahmed E. Hassan Queen's University
Bram Adams
Bram Adams Queen's University
Weiyi Shang
Weiyi Shang University of Waterloo
Emad Shihab
Emad Shihab Concordia University
Richard C. Holt
Richard C. Holt De Montfort University
Ying Zou
Ying Zou Queen's University
Meiyappan Nagappan
Meiyappan Nagappan University of Waterloo
Abram Hindle
Abram Hindle University of Alberta
Michael W. Godfrey
Michael W. Godfrey University of Waterloo
Marin Litoiu
Marin Litoiu York University

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