World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
7399
World Ranking
8015
National Ranking
10

Mike Papadakis 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 Mike Papadakis 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: 199 publications — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Mike Papadakis 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 Mike Papadakis 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Mike Papadakis is affiliated with the University of Luxembourg in Luxembourg and conducts research primarily in the field of Computer Science. Their work extensively covers several subfields, including Software, Artificial Intelligence, Information Systems, Computer Networks and Communications, and Signal Processing.

Their research spans a variety of topics, with a strong focus on Software Testing and Debugging Techniques, Software Engineering Research, Software Reliability and Analysis Research, Adversarial Robustness in Machine Learning, Software System Performance and Reliability, Topic Modeling, and Advanced Malware Detection Techniques.

Among their recent publications are:

  • Test Selection for Deep Learning Systems (2021), published in ACM Transactions on Software Engineering and Methodology
  • Improving machine translation systems via isotopic replacement (2022), Proceedings of the 44th International Conference on Software Engineering
  • An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement (2022), ACM Transactions on Software Engineering and Methodology
  • Safety and efficacy of arimoclomol for inclusion body myositis: a multicentre, randomised, double-blind, placebo-controlled trial (2023), The Lancet Neurology
  • Killing Stubborn Mutants with Symbolic Execution (2021), Open Repository and Bibliography (University of Luxembourg)

They have frequently collaborated with several researchers including Yves Le Traon, Maxime Cordy, Yuejun Guo, Renzo Degiovanni, and Qiang Hu, indicating a consistent engagement in cooperative research efforts.

Mike Papadakis publishes in a range of venues with multiple publications in arXiv (Cornell University), ACM Transactions on Software Engineering and Methodology, IEEE Transactions on Software Engineering, Empirical Software Engineering, and Proceedings of the 44th International Conference on Software Engineering.

They have also contributed to academic literature through book publications, notably a book titled Search-Based Software Engineering released in 2022 by Springer Science+Business Media.

Best Publications

  • Mutation Testing Advances: An Analysis and Survey

    Mike Papadakis;Marinos Kintis;Jie Zhang;Yue Jia

  • Static analysis of android apps

    Li Li;Tegawend F. Bissyand;Mike Papadakis;Siegfried Rasthofer

  • Metallaxis-FL: mutation-based fault localization

    Mike Papadakis;Yves Le Traon

  • Bypassing the Combinatorial Explosion: Using Similarity to Generate and Prioritize T-Wise Test Configurations for Software Product Lines

    Christopher Henard;Mike Papadakis;Gilles Perrouin;Jacques Klein

  • PIT: a practical mutation testing tool for Java (demo)

    Henry Coles;Thomas Laurent;Christopher Henard;Mike Papadakis

  • Comparing white-box and black-box test prioritization

    Christopher Henard;Mike Papadakis;Mark Harman;Yue Jia

  • Semantic fuzzing with zest

    Rohan Padhye;Caroline Lemieux;Koushik Sen;Mike Papadakis

  • Trivial compiler equivalence: a large scale empirical study of a simple, fast and effective equivalent mutant detection technique

    Mike Papadakis;Yue Jia;Mark Harman;Yves Le Traon

  • Combining multi-objective search and constraint solving for configuring large software product lines

    Christopher Henard;Mike Papadakis;Mark Harman;Yves Le Traon

  • An empirical study on mutation, statement and branch coverage fault revelation that avoids the unreliable clean program assumption

    Thierry Titcheu Chekam;Mike Papadakis;Yves Le Traon;Mark Harman

  • Automatic Mutation Test Case Generation via Dynamic Symbolic Execution

    Mike Papadakis;Nicos Malevris

  • An Empirical Evaluation of the First and Second Order Mutation Testing Strategies

    Mike Papadakis;Nicos Malevris

  • Multi-objective test generation for software product lines

    Christopher Henard;Mike Papadakis;Gilles Perrouin;Jacques Klein

  • Threats to the validity of mutation-based test assessment

    Mike Papadakis;Christopher Henard;Mark Harman;Yue Jia

  • PIT a Practical Mutation Testing Tool for Java

    Henry Coles;Thomas Laurent;Christopher Henard;Mike Papadakis

  • Evaluating Mutation Testing Alternatives: A Collateral Experiment

    Marinos Kintis;Mike Papadakis;Nicos Malevris

  • Using Mutants to Locate "Unknown" Faults

    Mike Papadakis;Yves Le Traon

  • A Replicable Comparison Study of NER Software: StanfordNLP, NLTK, OpenNLP, SpaCy, Gate

    Xavier Schmitt;Sylvain Kubler;Jeremy Robert;Mike Papadakis

  • Are mutation scores correlated with real fault detection?: a large scale empirical study on the relationship between mutants and real faults

    Mike Papadakis;Donghwan Shin;Shin Yoo;Doo-Hwan Bae

  • Detecting Trivial Mutant Equivalences via Compiler Optimisations

    Marinos Kintis;Mike Papadakis;Yue Jia;Nicos Malevris

  • Validity fuzzing and parametric generators for effective random testing

    Rohan Padhye;Caroline Lemieux;Koushik Sen;Mike Papadakis

Frequent Co-Authors

Yves Le Traon
Yves Le Traon University of Luxembourg
Jacques Klein
Jacques Klein University of Luxembourg
Mark Harman
Mark Harman University College London
Tegawendé F. Bissyandé
Tegawendé F. Bissyandé University of Luxembourg
Koushik Sen
Koushik Sen University of California, Berkeley
Yue Jia
Yue Jia University College London
Patrick Heymans
Patrick Heymans University of Namur
Axel Legay
Axel Legay Université Catholique de Louvain
Shin Yoo
Shin Yoo Korea Advanced Institute of Science and Technology
Lu Zhang
Lu Zhang Peking University

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