World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
6003
World Ranking
9373
National Ranking
3975

Julian Dolby 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 Julian Dolby 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: 142 publications — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Julian Dolby 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 Julian Dolby 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: 40 D-Index — 37th percentile

37% of scientists in this discipline score the same or lower.

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

Overview

Julian Dolby is affiliated with IBM in the United States and has an extensive publication record primarily in the field of Computer Science, with a focus on Artificial Intelligence and Information Systems. The research covers several subfields including Software, Signal Processing, and Management Science and Operations Research.

The scientist's research topics include Software Engineering Research, Computational Physics and Python Applications, Machine Learning and Data Classification, Topic Modeling, Software Testing and Debugging Techniques, Natural Language Processing Techniques, and Data Quality and Management.

Julian Dolby has contributed multiple papers to various respected venues. Some notable recent papers include:

  • CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks, 2021, published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Static Analysis of Shape in TensorFlow Programs, 2020, published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • A scalable AutoML approach based on graph neural networks, 2022, published in Proceedings of the VLDB Endowment
  • Program analysis using WALA (tutorial), 2022, published in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • Can Machines Read Coding Manuals Yet? - A Benchmark for Building Better Language Models for Code Understanding, 2022, published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequently collaborating with other researchers, Julian Dolby's notable coauthors include Kavitha Srinivas, Ibrahim Abdelaziz, Horst Samulowitz, Mossad Helali, and Essam Mansour. The collaboration count ranges from three to eleven papers with these coauthors.

The primary publication venues for Julian Dolby's works encompass:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the VLDB Endowment
  • Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • Proceedings of the AAAI Conference on Artificial Intelligence

The publication record reflects a strong interdisciplinary approach with a concentration on advancing toolsets and datasets for software engineering and AI-related challenges. Julian Dolby's work contributes to both foundational aspects and practical applications within these domains.

Best Publications

  • The Jikes research virtual machine project: building an open-source research community

    B. Alpern;S. Augart;S. M. Blackburn;M. Butrico

  • Associating synchronization constraints with data in an object-oriented language

    Mandana Vaziri;Frank Tip;Julian Dolby

  • Building an efficient RDF store over a relational database

    Mihaela A. Bornea;Julian Dolby;Anastasios Kementsietsidis;Kavitha Srinivas

  • A framework for automated testing of javascript web applications

    Shay Artzi;Julian Dolby;Simon Holm Jensen;Anders Moller

  • Finding Bugs in Web Applications Using Dynamic Test Generation and Explicit-State Model Checking

    S Artzi;A Kiezun;J Dolby;F Tip

  • Finding bugs in dynamic web applications

    Shay Artzi;Adam Kiezun;Julian Dolby;Frank Tip

  • Directed test generation for effective fault localization

    Shay Artzi;Julian Dolby;Frank Tip;Marco Pistoia

  • Saving the world wide web from vulnerable JavaScript

    Salvatore Guarnieri;Marco Pistoia;Omer Tripp;Julian Dolby

  • Correlation tracking for points-to analysis of javascript

    Manu Sridharan;Julian Dolby;Satish Chandra;Max Schäfer

  • CLAP: recording local executions to reproduce concurrency failures

    Jeff Huang;Charles Zhang;Julian Dolby

  • Efficient construction of approximate call graphs for JavaScript IDE services

    Asger Feldthaus;Max Schafer;Manu Sridharan;Julian Dolby

  • Alias analysis for object-oriented programs

    Manu Sridharan;Satish Chandra;Julian Dolby;Stephen J. Fink

  • Scalable and precise taint analysis for Android

    Wei Huang;Yao Dong;Ana Milanova;Julian Dolby

  • Race detection for web applications

    Boris Petrov;Martin Vechev;Manu Sridharan;Julian Dolby

  • An automatic object inlining optimization and its evaluation

    Julian Dolby;Andrew Chien

  • Dynamic detection of atomic-set-serializability violations

    Christian Hammer;Julian Dolby;Mandana Vaziri;Frank Tip

  • Matching patient records to clinical trials using ontologies

    Chintan Patel;James Cimino;Julian Dolby;Achille Fokoue

  • Practical fault localization for dynamic web applications

    Shay Artzi;Julian Dolby;Frank Tip;Marco Pistoia

  • Scalable semantic retrieval through summarization and refinement

    Julian Dolby;Achille Fokoue;Aditya Kalyanpur;Aaron Kershenbaum

  • MemSAT: checking axiomatic specifications of memory models

    Emina Torlak;Mandana Vaziri;Julian Dolby

Frequent Co-Authors

Frank Tip
Frank Tip Northeastern University
Marco Pistoia
Marco Pistoia JPMorgan Chase & Co (United States)
Manu Sridharan
Manu Sridharan University of California, Riverside
Anastasios Kementsietsidis
Anastasios Kementsietsidis Google (United States)
Aditya Kalyanpur
Aditya Kalyanpur Elemental Cognition
Stephen J. Fink
Stephen J. Fink Facebook (United States)
Vijay Karamcheti
Vijay Karamcheti New York University
Vivek Sarkar
Vivek Sarkar Georgia Institute of Technology
Barbara G. Ryder
Barbara G. Ryder Virginia Tech
Jan Vitek
Jan Vitek Northeastern University

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