World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
18860
World Ranking
2723
National Ranking
1354

John Shalf 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 John Shalf 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: 291 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

John Shalf 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 John Shalf 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: 63 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

John Shalf is affiliated with Lawrence Berkeley National Laboratory in the United States. Their research focuses primarily on computer science and engineering, with significant contributions in subfields such as electrical and electronic engineering, computer networks and communications, hardware and architecture, artificial intelligence, and information systems.

The main topics covered in their work include:

  • Parallel Computing and Optimization Techniques
  • Advanced Data Storage Technologies
  • Cloud Computing and Resource Management
  • Photonic and Optical Devices
  • Optical Network Technologies
  • Distributed and Parallel Computing Systems
  • Neural Networks and Reservoir Computing

John Shalf has contributed to various publication venues, with frequent publications in:

  • Computing in Science & Engineering
  • arXiv (Cornell University)
  • ACM Transactions on Architecture and Code Optimization
  • Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • Journal of Optical Communications and Networking

Selected recent papers authored or co-authored by John Shalf include:

  • The future of computing beyond Moore's Law, 2020, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • A Case For Intra-rack Resource Disaggregation in HPC, 2022, ACM Transactions on Architecture and Code Optimization
  • PINE: Photonic Integrated Networked Energy efficient datacenters (ENLITENED Program) [Invited], 2020, Journal of Optical Communications and Networking
  • Temporal Computing With Superconductors, 2021, IEEE Micro
  • Peta-Scale Embedded Photonics Architecture for Distributed Deep Learning Applications, 2023, Journal of Lightwave Technology

Frequent co-authors who have collaborated with John Shalf include:

  • George Michelogiannakis
  • Keren Bergman
  • Madeleine Glick
  • Larry Dennison
  • Anastasiia Butko

Best Publications

  • The Landscape of Parallel Computing Research: A View from Berkeley

    Krste Asanovic;Ras Bodik;Bryan Christopher Catanzaro;Joseph James Gebis

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • Optimization of sparse matrix-vector multiplication on emerging multicore platforms

    Samuel Williams;Leonid Oliker;Richard Vuduc;John Shalf

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • Performance Analysis of High Performance Computing Applications on the Amazon Web Services Cloud

    Keith R. Jackson;Lavanya Ramakrishnan;Krishna Muriki;Shane Canon

  • Stencil computation optimization and auto-tuning on state-of-the-art multicore architectures

    Kaushik Datta;Mark Murphy;Vasily Volkov;Samuel Williams

  • Exascale computing technology challenges

    John Shalf;Sudip Dosanjh;John Morrison

  • The potential of the cell processor for scientific computing

    Samuel Williams;John Shalf;Leonid Oliker;Shoaib Kamil

  • The future of computing beyond Moore's Law.

    John Shalf

  • The cactus framework and toolkit: design and applications

    Tom Goodale;Gabrielle Allen;Gerd Lanfermann;Joan Massó

  • Memory Errors in Modern Systems: The Good, The Bad, and The Ugly

    Vilas Sridharan;Nathan DeBardeleben;Sean Blanchard;Kurt B. Ferreira

  • Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors

    Kaushik Datta;Shoaib Kamil;Samuel Williams;Leonid Oliker

  • The Cactus framework and toolkit: Design and applications

    Tom Goodale;Gabrielle Allen;Gerd Lanfermann;Joan Masso

  • An auto-tuning framework for parallel multicore stencil computations

    Shoaib Kamil;Cy Chan;Leonid Oliker;John Shalf

  • The Cactus Worm: Experiments with Dynamic Resource Discovery and Allocation in a Grid Environment

    Gabrielle Allen;David Angulo;Ian Foster;Gerd Lanfermann

  • Computing beyond Moore's Law

    John M. Shalf;Robert Leland

  • Enabling Applications on the Grid: A Gridlab Overview

    Gabrielle Allen;Tom Goodale;Thomas Radke;Michael Russell

  • DOE Advanced Scientific Computing Advisory Subcommittee (ASCAC) Report: Top Ten Exascale Research Challenges

    Robert Lucas;James Ang;Keren Bergman;Shekhar Borkar

  • Implicit and explicit optimizations for stencil computations

    Shoaib Kamil;Kaushik Datta;Samuel Williams;Leonid Oliker

  • Using IOR to analyze the I/O Performance for HPC Platforms

    Hongzhang Shan;John Shalf

Frequent Co-Authors

Leonid Oliker
Leonid Oliker Lawrence Berkeley National Laboratory
Samuel Williams
Samuel Williams Lawrence Berkeley National Laboratory
Katherine Yelick
Katherine Yelick University of California, Berkeley
Shoaib Kamil
Shoaib Kamil Adobe Systems (United States)
Edward Seidel
Edward Seidel University of Wyoming
Keren Bergman
Keren Bergman Columbia University
Kurt Stockinger
Kurt Stockinger Zurich University of Applied Sciences
Mahmut Kandemir
Mahmut Kandemir Pennsylvania State University
Bernd Hamann
Bernd Hamann University of California, Davis
Michael F. Wehner
Michael F. Wehner Lawrence Berkeley National Laboratory

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