World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
10124
World Ranking
7855
National Ranking
3398

Nate Foster 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 Nate Foster 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: 114 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Nate Foster 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 Nate Foster 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Nate Foster is affiliated with Cornell University in the United States and has focused their research primarily in the field of Computer Science. Their work spans several subfields including Computer Networks and Communications, Hardware and Architecture, Artificial Intelligence, Software, and Computational Theory and Mathematics.

Their research addresses key topics such as Software Testing and Debugging Techniques, Formal Methods in Verification, Software-Defined Networks and 5G, Parallel Computing and Optimization Techniques, Network Packet Processing and Optimization, Security and Verification in Computing, and Embedded Systems Design Techniques.

Among their recent publications are:

  • Using deep programmability to put network owners in control, 2020, ACM SIGCOMM Computer Communication Review
  • Dependently-typed data plane programming, 2022, Proceedings of the ACM on Programming Languages
  • Lenses for Web Data, 2024, Technische Universität Berlin - Universitätsbibliothek
  • Formal Abstractions for Packet Scheduling, 2023, Proceedings of the ACM on Programming Languages
  • KATch: A Fast Symbolic Verifier for NetKAT, 2024, Proceedings of the ACM on Programming Languages

The scientist collaborates regularly with several co-authors. Frequent collaborators include Tobias Kappé, Dexter Kozen, Eric Hayden Campbell, Ryan Doenges, and Jana Wagemaker.

Publication venues where their research appears often include:

  • Proceedings of the ACM on Programming Languages
  • arXiv (Cornell University)
  • Artifact Digital Object Group
  • ACM SIGCOMM Computer Communication Review
  • Technische Universität Berlin - Universitätsbibliothek

Best Publications

  • Frenetic: a network programming language

    Nate Foster;Rob Harrison;Michael J. Freedman;Christopher Monsanto

  • Abstractions for network update

    Mark Reitblatt;Nate Foster;Jennifer Rexford;Cole Schlesinger

  • Composing software-defined networks

    Christopher Monsanto;Joshua Reich;Nate Foster;Jennifer Rexford

  • NetCache: Balancing Key-Value Stores with Fast In-Network Caching

    Xin Jin;Xiaozhou Li;Haoyu Zhang;Robert Soulé

  • NetKAT: semantic foundations for networks

    Carolyn Jane Anderson;Nate Foster;Arjun Guha;Jean-Baptiste Jeannin

  • Mechanized metatheory for the masses: the PoplMark challenge

    Brian E. Aydemir;Aaron Bohannon;Matthew Fairbairn;J. Nathan Foster

  • Bidirectional Transformations: A Cross-Discipline Perspective

    Krzysztof Czarnecki;J. Nathan Foster;Zhenjiang Hu;Ralf Lämmel

  • A compiler and run-time system for network programming languages

    Christopher Monsanto;Nate Foster;Rob Harrison;David Walker

  • Consistent updates for software-defined networks: change you can believe in!

    Mark Reitblatt;Nate Foster;Jennifer Rexford;David Walker

  • Languages for software-defined networks

    N. Foster;A. Guha;M. Reitblatt;A. Story

  • FatTire: declarative fault tolerance for software-defined networks

    Mark Reitblatt;Marco Canini;Arjun Guha;Nate Foster

  • Boomerang: resourceful lenses for string data

    Aaron Bohannon;J. Nathan Foster;Benjamin C. Pierce;Alexandre Pilkiewicz

  • Modular SDN Programming with Pyretic

    Joshua Reich;Christopher Monsanto;Nate Foster;Jennifer Rexford

  • Combinators for bi-directional tree transformations: a linguistic approach to the view update problem

    J. Nathan Foster;Michael B. Greenwald;Jonathan T. Moore;Benjamin C. Pierce

  • Merlin: A Language for Provisioning Network Resources

    Robert Soulé;Shrutarshi Basu;Parisa Jalili Marandi;Fernando Pedone

  • Netchain: scale-free sub-RTT coordination

    Xin Jin;Xiaozhou Li;Haoyu Zhang;Nate Foster

  • P4FPGA: A Rapid Prototyping Framework for P4

    Han Wang;Robert Soulé;Huynh Tu Dang;Ki Suh Lee

  • Splendid isolation: a slice abstraction for software-defined networks

    Stephen Gutz;Alec Story;Cole Schlesinger;Nate Foster

  • Abstractions for software-defined networks

    Martin Casado;Nate Foster;Arjun Guha

  • Efficient synthesis of network updates

    Jedidiah McClurg;Hossein Hojjat;Pavol Černý;Nate Foster

  • Semi-Oblivious Traffic Engineering: The Road Not Taken.

    Praveen Kumar;Yang Yuan;Chris Yu;Nate Foster

Frequent Co-Authors

Dexter Kozen
Dexter Kozen Cornell University
David Walker
David Walker Princeton University
Jennifer Rexford
Jennifer Rexford Princeton University
Robert Kleinberg
Robert Kleinberg Cornell University
Emin Gün Sirer
Emin Gün Sirer Cornell University
Jeongkeun Lee
Jeongkeun Lee Intel (United States)
Changhoon Kim
Changhoon Kim Intel (United States)
Johannes Gehrke
Johannes Gehrke Microsoft (United States)
Michael J. Freedman
Michael J. Freedman Princeton University
James Cheney
James Cheney University of Edinburgh

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