World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
8089
World Ranking
6234
National Ranking
246

Emad Shihab 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 Emad Shihab 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: 133 publications — 20th percentile

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

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

Emad Shihab 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 Emad Shihab 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Emad Shihab is affiliated with Concordia University in Canada, focusing on research within the broad field of Computer Science. Their work spans numerous subfields, including Information Systems, Artificial Intelligence, Computer Science Applications, Computer Networks and Communications, and Signal Processing.

The main topics of Emad Shihab's research include Software Engineering Research, AI in Service Interactions, Open Source Software Innovations, Software System Performance and Reliability, Advanced Malware Detection Techniques, Software Engineering Techniques and Practices, and Software Reliability and Analysis Research.

They have contributed to several recent publications that highlight key areas of their work:

  • "A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering," 2021, IEEE Transactions on Software Engineering
  • "What do Programmers Discuss about Deep Learning Frameworks," 2020, Empirical Software Engineering
  • "A Machine Learning Approach to Improve the Detection of CI Skip Commits," 2020, IEEE Transactions on Software Engineering
  • "Empirical analysis of security vulnerabilities in Python packages," 2023, Empirical Software Engineering
  • "Dependency Smells in JavaScript Projects," 2021, IEEE Transactions on Software Engineering

Frequent collaborators in Emad Shihab's research include:

  • Diego Elias Costa
  • Rabe Abdalkareem
  • Ahmad Abdellatif
  • Khaled Badran
  • Suhaib Mujahid

Their research has been published across multiple venues, notably:

  • Zenodo (CERN European Organization for Nuclear Research)
  • arXiv (Cornell University)
  • IEEE Transactions on Software Engineering
  • Empirical Software Engineering
  • OPAL (Open@LaTrobe) (La Trobe University)

Best Publications

  • A large-scale empirical study of just-in-time quality assurance

    Y. Kamei;E. Shihab;B. Adams;A. E. Hassan

  • What Do Mobile App Users Complain About

    Hammad Khalid;Emad Shihab;Meiyappan Nagappan;Ahmed E. Hassan

  • What are mobile developers asking about? A large scale study using stack overflow

    Christoffer Rosen;Emad Shihab

  • An Exploratory Study on Self-Admitted Technical Debt

    Aniket Potdar;Emad Shihab

  • Using Natural Language Processing to Automatically Detect Self-Admitted Technical Debt

    Everton da Silva Maldonado;Emad Shihab;Nikolaos Tsantalis

  • Identifying self-admitted technical debt in open source projects using text mining

    Qiao Huang;Emad Shihab;Xin Xia;Xin Xia;David Lo

  • Why do developers use trivial packages? an empirical case study on npm

    Rabe Abdalkareem;Olivier Nourry;Sultan Wehaibi;Suhaib Mujahid

  • Studying re-opened bugs in open source software

    Emad Shihab;Akinori Ihara;Yasutaka Kamei;Walid M. Ibrahim

  • An industrial study on the risk of software changes

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

  • Detecting and quantifying different types of self-admitted technical Debt

    Everton da S. Maldonado;Emad Shihab

  • Commit guru: analytics and risk prediction of software commits

    Christoffer Rosen;Ben Grawi;Emad Shihab

  • Future Trends in Software Engineering Research for Mobile Apps

    Meiyappan Nagappan;Emad Shihab

  • Predicting Re-opened Bugs: A Case Study on the Eclipse Project

    Emad Shihab;Akinori Ihara;Yasutaka Kamei;Walid M. Ibrahim

  • Defect Prediction: Accomplishments and Future Challenges

    Yasutaka Kamei;Emad Shihab

  • Characterizing and predicting blocking bugs in open source projects

    Harold Valdivia Garcia;Emad Shihab

  • Examining the Impact of Self-Admitted Technical Debt on Software Quality

    Sultan Wehaibi;Emad Shihab;Latifa Guerrouj

  • 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

  • High-impact defects: a study of breakage and surprise defects

    Emad Shihab;Audris Mockus;Yasutaka Kamei;Bram Adams

  • On code reuse from StackOverflow

    Rabe Abdalkareem;Emad Shihab;Juergen Rilling

  • A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors.

    Akbar Dehghani;Omid Sarbishei;Tristan Glatard;Emad Shihab

  • Prioritizing the devices to test your app on: a case study of Android game apps

    Hammad Khalid;Meiyappan Nagappan;Emad Shihab;Ahmed E. Hassan

Frequent Co-Authors

Ahmed E. Hassan
Ahmed E. Hassan Queen's University
Xin Xia
Xin Xia Huawei Technologies (China)
Bram Adams
Bram Adams Queen's University
David Lo
David Lo Singapore Management University
Yasutaka Kamei
Yasutaka Kamei Kyushu University
Zhen Ming Jiang
Zhen Ming Jiang York University
Meiyappan Nagappan
Meiyappan Nagappan University of Waterloo
Weiyi Shang
Weiyi Shang University of Waterloo
Lin Cai
Lin Cai Illinois Institute of Technology
Jianping Pan
Jianping Pan University of Victoria

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