World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
74
Citations
28135
World Ranking
1465
National Ranking
763

Vitaly Shmatikov 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 Vitaly Shmatikov 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: 149 publications — 26th percentile

26% of scientists in this discipline score the same or lower.

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

Vitaly Shmatikov 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 Vitaly Shmatikov 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: 74 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Overview

Vitaly Shmatikov is affiliated with Cornell University in the United States and has a significant research output primarily in the field of computer science. Their work spans multiple areas including artificial intelligence, information systems, computer vision, and sociology and political science, with a dominant focus on artificial intelligence.

The research topics covered by Vitaly Shmatikov include:

  • Adversarial Robustness in Machine Learning
  • Topic Modeling
  • Natural Language Processing Techniques
  • Anomaly Detection Techniques and Applications
  • Security and Verification in Computing
  • Explainable Artificial Intelligence (XAI)
  • Privacy, Security, and Data Protection

The scientist has published extensively, with publications concentrated in venues such as arXiv affiliated with Cornell University. Other venues include the 2022 IEEE Symposium on Security and Privacy (SP), Proceedings on Privacy Enhancing Technologies, and SSRN Electronic Journal. The research at these venues often addresses emerging challenges in machine learning, security, and privacy.

Recent representative papers include:

  • Salvaging Federated Learning by Local Adaptation (2020, arXiv - Cornell University)
  • Blind Backdoors in Deep Learning Models (2020, arXiv - Cornell University)
  • Spinning Language Models: Risks of Propaganda-As-A-Service and Countermeasures (2022, IEEE Symposium on Security and Privacy)
  • You Autocomplete Me: Poisoning Vulnerabilities in Neural Code Completion (2020, arXiv - Cornell University)
  • Abusing Images and Sounds for Indirect Instruction Injection in Multi-Modal LLMs (2023, arXiv - Cornell University)

Frequent collaborators in research include Eugene Bagdasaryan, John X. Morris, Roei Schuster, Alexander M. Rush, and Collin Zhang, highlighting a network of coauthors also engaged in topics related to machine learning security and privacy.

Best Publications

  • Membership Inference Attacks Against Machine Learning Models

    Reza Shokri;Marco Stronati;Congzheng Song;Vitaly Shmatikov

  • Robust De-anonymization of Large Sparse Datasets

    A. Narayanan;V. Shmatikov

  • Privacy-Preserving Deep Learning

    Reza Shokri;Vitaly Shmatikov

  • De-anonymizing Social Networks

    Arvind Narayanan;Vitaly Shmatikov

  • Exploiting Unintended Feature Leakage in Collaborative Learning

    Luca Melis;Congzheng Song;Emiliano De Cristofaro;Vitaly Shmatikov

  • How To Backdoor Federated Learning.

    Eugene Bagdasaryan;Andreas Veit;Yiqing Hua;Deborah Estrin

  • Airavat: security and privacy for MapReduce

    Indrajit Roy;Srinath T. V. Setty;Ann Kilzer;Vitaly Shmatikov

  • The most dangerous code in the world: validating SSL certificates in non-browser software

    Martin Georgiev;Subodh Iyengar;Suman Jana;Rishita Anubhai

  • Fast dictionary attacks on passwords using time-space tradeoff

    Arvind Narayanan;Vitaly Shmatikov

  • Myths and fallacies of "Personally Identifiable Information"

    Arvind Narayanan;Vitaly Shmatikov

  • Machine Learning Models that Remember Too Much

    Congzheng Song;Thomas Ristenpart;Vitaly Shmatikov

  • Constraint solving for bounded-process cryptographic protocol analysis

    Jonathan Millen;Vitaly Shmatikov

  • The cost of privacy: destruction of data-mining utility in anonymized data publishing

    Justin Brickell;Vitaly Shmatikov

  • Privacy-preserving graph algorithms in the semi-honest model

    Justin Brickell;Vitaly Shmatikov

  • "You Might Also Like:" Privacy Risks of Collaborative Filtering

    Joseph A. Calandrino;Ann Kilzer;Arvind Narayanan;Edward W. Felten

  • Timing Analysis in Low-Latency Mix Networks : Attacks and Defenses

    Vitaly Shmatikov;Ming-Hsiu Wang

  • How To Break Anonymity of the Netflix Prize Dataset

    Arvind Narayanan;Vitaly Shmatikov

  • Finite-state analysis of SSL 3.0

    John C. Mitchell;Vitaly Shmatikov;Ulrich Stern

  • Towards Practical Privacy for Genomic Computation

    S. Jha;L. Kruger;V. Shmatikov

  • Information hiding, anonymity and privacy: a modular approach

    Dominic Hughes;Vitaly Shmatikov

  • Differential Privacy Has Disparate Impact on Model Accuracy

    Eugene Bagdasaryan;Omid Poursaeed;Vitaly Shmatikov

  • Privacy and Security Myths and Fallacies of Personally Identifiable Information

    Arvind Narayanan;Vitaly Shmatikov

Frequent Co-Authors

Suman Jana
Suman Jana Columbia University
Thomas Ristenpart
Thomas Ristenpart Cornell University
John C. Mitchell
John C. Mitchell Stanford University
Arvind Narayanan
Arvind Narayanan Princeton University
Stanislaw Jarecki
Stanislaw Jarecki University of California, Irvine
Reza Shokri
Reza Shokri National University of Singapore
Emmett Witchel
Emmett Witchel The University of Texas at Austin
Gethin Norman
Gethin Norman University of Glasgow
Kathryn S. McKinley
Kathryn S. McKinley Google (United States)
Amir Houmansadr
Amir Houmansadr University of Massachusetts Amherst

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