World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
13597
World Ranking
8600
National Ranking
63

Kai Petersen 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 Kai Petersen 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: 152 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Kai Petersen 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 Kai Petersen 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: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Kai Petersen is affiliated with the Blekinge Institute of Technology in Sweden. Their research primarily spans the field of Computer Science, with a strong focus on Information Systems and Software. Additional areas of study include Artificial Intelligence, Computer Science Applications, and Biomedical Engineering.

Their work covers topics related to software engineering techniques and practices, software engineering research, software testing and debugging techniques, open source software innovations, advanced software engineering methodologies, semantic web and ontologies, and scientific computing and data management.

Notable recent papers authored or coauthored by Kai Petersen include:

  • #Covid-19: An exploratory investigation of hashtag usage on Twitter (2021, Health Policy)
  • Context checklist for industrial software engineering research and practice (2021, Computer Standards & Interfaces)

Frequent collaborators in their research include:

  • Jürgen Börstler
  • Mohsin Irshad
  • Nauman bin Ali
  • Emília Mendes
  • Nasir Mehmood Minhas

Petersen's publications often appear in the following venues:

  • Information and Software Technology
  • Journal of Systems and Software
  • e-Informatica Software Engineering Journal
  • SSRN Electronic Journal
  • arXiv (Cornell University)

Best Publications

  • Systematic mapping studies in software engineering

    Kai Petersen;Robert Feldt;Shahid Mujtaba;Michael Mattsson

  • Guidelines for conducting systematic mapping studies in software engineering : An update

    Kai Petersen;Sairam Vakkalanka;Ludwik Kuzniarz

  • Context in industrial software engineering research

    Kai Petersen;Claes Wohlin

  • Benefits and limitations of automated software testing: systematic literature review and practitioner survey

    Dudekula Mohammad Rafi;Katam Reddy Kiran Moses;Kai Petersen;Mika V. Mantyla

  • What is DevOps?: A Systematic Mapping Study on Definitions and Practices

    Ramtin Jabbari;Nauman bin Ali;Kai Petersen;Binish Tanveer

  • A comparison of issues and advantages in agile and incremental development between state of the art and an industrial case

    Kai Petersen;Claes Wohlin

  • The Waterfall Model in Large-Scale Development

    Kai Petersen;Kai Petersen;Claes Wohlin;Dejan Baca;Dejan Baca

  • The effect of moving from a plan-driven to an incremental software development approach with agile practices

    Kai Petersen;Claes Wohlin

  • Challenges and best practices in industry-academia collaborations in software engineering

    Vahid Garousi;Kai Petersen;Baris Ozkan

  • Experiences from using snowballing and database searches in systematic literature studies

    Deepika Badampudi;Claes Wohlin;Kai Petersen

  • Worldviews, Research Methods, and their Relationship to Validity in Empirical Software Engineering Research

    Kai Petersen;Cigdem Gencel

  • Measuring the flow in lean software development

    K. Petersen;C. Wohlin

  • Measuring and predicting software productivity

    Kai Petersen

  • On rapid releases and software testing: a case study and a semi-systematic literature review

    Mika V. Mäntylä;Bram Adams;Foutse Khomh;Emelie Engström

  • Software process improvement through the Lean Measurement (SPI-LEAM) method

    Kai Petersen;Claes Wohlin

  • Vision based victim detection from unmanned aerial vehicles

    Mykhaylo Andriluka;Paul Schnitzspan;Johannes Meyer;Stefan Kohlbrecher

  • Considering rigor and relevance when evaluating test driven development: A systematic review

    Hussan Munir;Misagh Moayyed;Kai Petersen

  • Survey Guidelines in Software Engineering: An Annotated Review

    Jefferson Seide Molléri;Kai Petersen;Emilia Mendes

  • Action research as a model for industry-academia collaboration in the software engineering context

    Kai Petersen;Cigdem Gencel;Negin Asghari;Dejan Baca

  • Waste and Lead Time Reduction in a Software Product Customization Process with Value Stream Maps

    Shahid Mujtaba;Robert Feldt;Kai Petersen

  • A systematic literature review on the industrial use of software process simulation

    Nauman Bin Ali;Kai Petersen;Claes Wohlin

  • Prioritizing agile benefits and limitations in relation to practice usage

    Adam Solinski;Kai Petersen

  • Benefits and Limitations of Automated Software Testing Systematic Literature Review and Practitioner Survey

    Dudekula Mohammad Rafi;Katam Reddy Kiran Moses;Kai Petersen;Mika Mäntylä

Frequent Co-Authors

Claes Wohlin
Claes Wohlin Blekinge Institute of Technology
Mika V. Mäntylä
Mika V. Mäntylä University of Helsinki
Emilia Mendes
Emilia Mendes Aarhus University
Tony Gorschek
Tony Gorschek Blekinge Institute of Technology
Robert Feldt
Robert Feldt Chalmers University of Technology
Dietmar Pfahl
Dietmar Pfahl University of Tartu
Michael Felderer
Michael Felderer University of Cologne
Richard Torkar
Richard Torkar University of Gothenburg
Per Runeson
Per Runeson Lund University
Foutse Khomh
Foutse Khomh Polytechnique Montréal

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