World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
17583
World Ranking
8574
National Ranking
3670

Ilya Mironov 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 Ilya Mironov 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: 80 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

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

Ilya Mironov 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 Ilya Mironov 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

Ilya Mironov is a researcher affiliated with Facebook in the United States, focusing on areas within computer science. Their work spans a variety of topics including privacy-preserving technologies, adversarial robustness in machine learning, and stochastic gradient optimization techniques. Mironov's research explores detailed aspects of data privacy and security, contributing notably to the development of methods and frameworks that enhance privacy protections in data processing and machine learning applications.

Mironov's publication record includes multiple contributions to well-regarded scientific venues such as arXiv (Cornell University), Leibniz-Zentrum für Informatik (Schloss Dagstuhl), and the Lecture Notes in Computer Science series. This reflects a consistent engagement with both pre-publication repositories and formal academic outlets.

Their recent papers include:

  • Information-Theoretic Single-Server PIR in the Shuffle Model, 2024, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Green Federated Learning, 2023, arXiv (Cornell University)
  • Opacus: User-Friendly Differential Privacy Library in PyTorch, 2021, arXiv (Cornell University)
  • Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation, 2020, arXiv (Cornell University)
  • Cryptanalytic Extraction of Neural Network Models, 2020, Lecture Notes in Computer Science

Their coauthors frequently include Ashkan Yousefpour, Mani Malek, Sayan Ghosh, Pierre Stock, and Úlfar Erlingsson. Collaboration with these researchers has resulted in several joint publications that demonstrate interlinked efforts within the fields of privacy, machine learning, and data security.

Mironov's research primarily falls within computer science, with a significant focus on artificial intelligence. Their work also intersects with computer science applications, sociology and political science, computer vision and pattern recognition, and electrical and electronic engineering.

The main topics addressed in their research are:

  • Privacy-Preserving Technologies in Data
  • Adversarial Robustness in Machine Learning
  • Stochastic Gradient Optimization Techniques
  • Mobile Crowdsensing and Crowdsourcing
  • Internet Traffic Analysis and Secure E-voting
  • Cryptography and Data Security
  • Advanced Neural Network Applications

Best Publications

  • Deep Learning with Differential Privacy

    Martin Abadi;Andy Chu;Ian Goodfellow;H. Brendan McMahan

  • Our data, ourselves : Privacy via distributed noise generation

    Cynthia Dwork;Krishnaram Kenthapadi;Frank Mcsherry;Ilya Mironov

  • Rényi Differential Privacy

    Ilya Mironov

  • Differentially private recommender systems: Building privacy into the Netflix Prize contenders

    Frank McSherry;Ilya Mironov

  • Incentives for sharing in peer-to-peer networks

    Philippe Golle;Kevin Leyton-Brown;Ilya Mironov

  • Incentives for Sharing in Peer-to-Peer Networks

    Philippe Golle;Kevin Leyton-Brown;Ilya Mironov;Mark Lillibridge

  • Cache-collision timing attacks against AES

    Joseph Bonneau;Ilya Mironov

  • Frodo: Take off the Ring! Practical, Quantum-Secure Key Exchange from LWE

    Joppe Bos;Craig Costello;Leo Ducas;Ilya Mironov

  • Prochlo: Strong Privacy for Analytics in the Crowd

    Andrea Bittau;Úlfar Erlingsson;Petros Maniatis;Ilya Mironov

  • Scalable Private Learning with PATE

    Nicolas Papernot;Shuang Song;Ilya Mironov;Ananth Raghunathan

  • Uncheatable Distributed Computations

    Philippe Golle;Ilya Mironov

  • Computational Differential Privacy

    Ilya Mironov;Omkant Pandey;Omer Reingold;Salil Vadhan

  • The Limits of Two-Party Differential Privacy.

    Andrew McGregor;Ilya Mironov;Toniann Pitassi;Omer Reingold

  • Applications of SAT Solvers to Cryptanalysis of Hash Functions.

    Ilya Mironov;Lintao Zhang

  • not so) random shuffles of RC4

    Ilya Mironov

  • On significance of the least significant bits for differential privacy

    Ilya Mironov

  • Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity

    Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan

  • Amplification by shuffling: from local to central differential privacy via anonymity

    Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan

  • Message-Locked Encryption for Lock-Dependent Messages.

    Martín Abadi;Dan Boneh;Ilya Mironov;Ananth Raghunathan

  • Cryptographic primitives enforcing communication and storage complexity

    Philippe Golle;Stanislaw Jarecki;Ilya Mironov

  • A General Approach to Adding Differential Privacy to Iterative Training Procedures

    Brendan McMahan;Galen Andrew;Ilya Mironov;Nicolas Papernot

  • Rényi Differential Privacy of the Sampled Gaussian Mechanism.

    Ilya Mironov;Kunal Talwar;Li Zhang

  • Differentially private recommender systems

    Frank McSherry;Ilya Mironov

Frequent Co-Authors

Kunal Talwar
Kunal Talwar Apple (United States)
Gil Segev
Gil Segev Hebrew University of Jerusalem
Ramarathnam Venkatesan
Ramarathnam Venkatesan Microsoft (United States)
Martín Abadi
Martín Abadi Google (United States)
Frank McSherry
Frank McSherry Materialize, Inc.
Abhradeep Thakurta
Abhradeep Thakurta Google (United States)
Omer Reingold
Omer Reingold Stanford University
Dan Boneh
Dan Boneh Stanford University
Vitaly Feldman
Vitaly Feldman Apple (United States)

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