World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
47
Citations
13356
World Ranking
6345
National Ranking
2833

Robert DeLine 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 Robert DeLine 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: 108 publications — 11th percentile

11% of scientists in this discipline score the same or lower.

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

Robert DeLine 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 Robert DeLine 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: 47 D-Index — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Overview

Robert DeLine is affiliated with Microsoft (United States) and conducts research primarily in the field of Computer Science. Their work spans several subfields including Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Information Systems and Management, and Computer Networks and Communications.

The main topics addressed in their research include Data Visualization and Analytics, Scientific Computing and Data Management, Software Engineering Research, Software System Performance and Reliability, Explainable Artificial Intelligence (XAI), Topic Modeling, and Data Analysis with R.

The scientist has published in a variety of venues, indicating a diverse range of research interests. These venues include:

  • arXiv (Cornell University)
  • ACM Transactions on Computer-Human Interaction
  • CHI Conference on Human Factors in Computing Systems
  • Proceedings of the ACM on software engineering.
  • Proceedings of the ACM on Human-Computer Interaction

Frequent collaborators in Robert DeLine's research include Steven M. Drucker, Carmen Badea, Christian Bird, Denae Ford, and Nicole Forsgren, each having co-authored multiple publications with them.

Notable recent papers authored or co-authored by Robert DeLine cover various aspects of human-computer interaction, machine learning, and software engineering. These include:

  • "What Did My AI Learn? How Data Scientists Make Sense of Model Behavior" (2022) published in ACM Transactions on Computer-Human Interaction
  • "Diff in the Loop: Supporting Data Comparison in Exploratory Data Analysis" (2022) presented at CHI Conference on Human Factors in Computing Systems
  • "How Teams Communicate about the Quality of ML Models: A Case Study at an International Technology Company" (2021) published in Proceedings of the ACM on Human-Computer Interaction
  • "Can GPT-4 Replicate Empirical Software Engineering Research?" (2024) published in Proceedings of the ACM on software engineering.
  • "GEMS: Generative Expert Metric System through Iterative Prompt Priming" (2024) available on arXiv (Cornell University)

Best Publications

  • Abstractions for software architecture and tools to support them

    M. Shaw;R. DeLine;D.V. Klein;T.L. Ross

  • Boogie: a modular reusable verifier for object-oriented programs

    Mike Barnett;Bor-Yuh Evan Chang;Robert DeLine;Bart Jacobs

  • Software engineering for machine learning: a case study

    Saleema Amershi;Andrew Begel;Christian Bird;Robert DeLine

  • Maintaining mental models: a study of developer work habits

    Thomas D. LaToza;Gina Venolia;Robert DeLine

  • Information Needs in Collocated Software Development Teams

    Andrew J. Ko;Robert DeLine;Gina Venolia

  • Enforcing high-level protocols in low-level software

    Robert DeLine;Manuel Fähndrich

  • Verification of object-oriented programs with invariants

    Michael Barnett;Robert DeLine;Manuel Fähndrich;K. Rustan M. Leino

  • Interactions with big data analytics

    Danyel Fisher;Rob DeLine;Mary Czerwinski;Steven Drucker

  • A field study of API learning obstacles

    Martin P. Robillard;Robert Deline

  • Boogie: a modular reusable verifier for object-oriented programs

    Mike Barnett;Bor-Yuh Evan Chang;Robert Deline;Bart Jacobs

  • Adoption and focus: practical linear types for imperative programming

    Manuel Fahndrich;Robert DeLine

  • Let's go to the whiteboard: how and why software developers use drawings

    Mauro Cherubini;Gina Venolia;Rob DeLine;Amy J. Ko

  • Typestates for Objects

    Robert DeLine;Manuel Fähndrich

  • The emerging role of data scientists on software development teams

    Miryung Kim;Thomas Zimmermann;Robert DeLine;Andrew Begel

  • Alice: Rapid prototyping system for virtual reality

    Randy Pausch;Tommy Burnette;A.C. Capeheart;Matthew Conway

  • Gamut: A Design Probe to Understand How Data Scientists Understand Machine Learning Models

    Fred Hohman;Andrew Head;Rich Caruana;Robert DeLine

  • Data Scientists in Software Teams: State of the Art and Challenges

    Miryung Kim;Thomas Zimmermann;Robert DeLine;Andrew Begel

  • Trill: a high-performance incremental query processor for diverse analytics

    Badrish Chandramouli;Jonathan Goldstein;Mike Barnett;Robert DeLine

  • BoogiePL: A typed procedural language for checking object-oriented programs

    Robert DeLine;K. Rustan M. Leino

  • Abstractions and implementations for architectural connections

    M. Shaw;R. DeLine;G. Zelesnik

Frequent Co-Authors

Steven M. Drucker
Steven M. Drucker Microsoft (United States)
Danyel Fisher
Danyel Fisher Microsoft (United States)
Gina Venolia
Gina Venolia Microsoft (United States)
Andrew Begel
Andrew Begel Carnegie Mellon University
Manuel Fähndrich
Manuel Fähndrich Google (United States)
Thomas Zimmermann
Thomas Zimmermann Microsoft (United States)
Mary Czerwinski
Mary Czerwinski Microsoft (United States)
Randy Pausch
Randy Pausch Carnegie Mellon University
Jonathan Goldstein
Jonathan Goldstein Microsoft (United States)
John Platt
John Platt Google (United States)

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