World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
11186
World Ranking
8634
National Ranking
3701

Philip J. Guo 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 Philip J. Guo 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: 102 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Philip J. Guo 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 Philip J. Guo 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

Philip J. Guo is affiliated with the University of California, San Diego in the United States. Their research spans multiple subfields within computer science, with a focus on areas such as computer vision and pattern recognition, information systems, electrical and electronic engineering, computer science applications, and artificial intelligence.

The primary topics Philip J. Guo investigates include data visualization and analytics, big data and business intelligence, ethics and social impacts of AI, online learning and analytics, machine learning and data classification, spreadsheets and end-user computing, and multimedia communication and technology.

Their recent scholarly output includes publications in various reputable venues, demonstrating a breadth of collaborative and interdisciplinary research. Notable papers by Philip J. Guo comprise:

  • "Six Opportunities for Scientists and Engineers to Learn Programming Using AI Tools Such as ChatGPT," 2023, Computing in Science & Engineering

Other recent articles featuring their work or close collaboration have appeared in venues such as:

  • Proceedings of the 53rd ACM Technical Symposium on Computer Science Education
  • Designing Interactive Systems Conference
  • Proceedings of the ACM on Programming Languages
  • arXiv (Cornell University)

Frequent coauthors include:

  • Sean Kross
  • Ian Drosos
  • Sam Lau
  • Deborah Nolan
  • Joseph E. Gonzalez

Philip J. Guo's work reflects a significant engagement with computer science topics as well as interdisciplinary themes connecting to social sciences, as indicated by their publication record spanning these fields. Their collaborative network and publication venues suggest active participation in computer science education research and computational methodologies.

Best Publications

  • How video production affects student engagement: an empirical study of MOOC videos

    Philip J. Guo;Juho Kim;Rob Rubin

  • The Daikon system for dynamic detection of likely invariants

    Michael D. Ernst;Jeff H. Perkins;Philip J. Guo;Stephen McCamant

  • Automatic creation of SQL Injection and cross-site scripting attacks

    Adam Kieyzun;Philip J. Guo;Karthick Jayaraman;Michael D. Ernst

  • Online python tutor: embeddable web-based program visualization for cs education

    Philip J. Guo

  • Two studies of opportunistic programming: interleaving web foraging, learning, and writing code

    Joel Brandt;Philip J. Guo;Joel Lewenstein;Mira Dontcheva

  • Understanding in-video dropouts and interaction peaks inonline lecture videos

    Juho Kim;Philip J. Guo;Daniel T. Seaton;Piotr Mitros

  • Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows

    Philip J. Guo;Thomas Zimmermann;Nachiappan Nagappan;Brendan Murphy

  • HAMPI: a solver for string constraints

    Adam Kiezun;Vijay Ganesh;Philip J. Guo;Pieter Hooimeijer

  • OverCode: Visualizing Variation in Student Solutions to Programming Problems at Scale

    Elena L. Glassman;Jeremy Scott;Rishabh Singh;Philip J. Guo

  • Characterizing and predicting which bugs get reopened

    Thomas Zimmermann;Nachiappan Nagappan;Philip J. Guo;Brendan Murphy

  • Data-driven interaction techniques for improving navigation of educational videos

    Juho Kim;Philip J. Guo;Carrie J. Cai;Shang-Wen (Daniel) Li

  • "Not my bug!" and other reasons for software bug report reassignments

    Philip J. Guo;Thomas Zimmermann;Nachiappan Nagappan;Brendan Murphy

  • Crowdsourcing step-by-step information extraction to enhance existing how-to videos

    Juho Kim;Phu Tran Nguyen;Sarah Weir;Philip J. Guo

  • Inference and enforcement of data structure consistency specifications

    Brian Demsky;Michael D. Ernst;Philip J. Guo;Stephen McCamant

  • Paradise unplugged: identifying barriers for female participation on stack overflow

    Denae Ford;Justin Smith;Philip J. Guo;Chris Parnin

  • Non-Native English Speakers Learning Computer Programming: Barriers, Desires, and Design Opportunities

    Philip J. Guo

  • Proactive wrangling: mixed-initiative end-user programming of data transformation scripts

    Philip J. Guo;Sean Kandel;Joseph M. Hellerstein;Jeffrey Heer

  • Opportunistic programming: how rapid ideation and prototyping occur in practice

    Joel Brandt;Philip J. Guo;Joel Lewenstein;Scott R. Klemmer

  • Codeopticon: Real-Time, One-To-Many Human Tutoring for Computer Programming

    Philip J. Guo

  • Wrex: A Unified Programming-by-Example Interaction for Synthesizing Readable Code for Data Scientists

    Ian Drosos;Titus Barik;Philip J. Guo;Robert DeLine

  • Crowdsourcing step-by-step information extraction to enhance existing how-to videos

    Phu Tran Nguyen;Sarah Weir;Philip J. Guo;Robert C. Miller

Frequent Co-Authors

Michael D. Ernst
Michael D. Ernst University of Washington
Scott R. Klemmer
Scott R. Klemmer University of California, San Diego
Krzysztof Z. Gajos
Krzysztof Z. Gajos Harvard University
Rishabh Singh
Rishabh Singh Google (United States)
Dawson Engler
Dawson Engler Stanford University
Thomas Zimmermann
Thomas Zimmermann Microsoft (United States)
Nachiappan Nagappan
Nachiappan Nagappan Facebook (United States)
Brendan Murphy
Brendan Murphy Microsoft (United States)
James D. Hollan
James D. Hollan University of California, San Diego

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