World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
5745
World Ranking
9835
National Ranking
4140

Vitaly Feldman 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 Feldman 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: 155 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Vitaly Feldman 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 Feldman 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

Vitaly Feldman is a researcher affiliated with Apple in the United States. Their academic focus is primarily within the field of Computer Science, with a significant concentration in Artificial Intelligence. Additional subfields of study include Statistics and Probability, Management Science and Operations Research, Computational Mechanics, and Computational Theory and Mathematics.

Their research spans several key topics, notably Privacy-Preserving Technologies in Data, Cryptography and Data Security, and Stochastic Gradient Optimization Techniques. Other areas of interest within their work include Internet Traffic Analysis and Secure E-voting, Adversarial Robustness in Machine Learning, Sparse and Compressive Sensing Techniques, and Complexity and Algorithms in Graphs.

Vitaly Feldman has contributed to multiple publications in various prestigious venues. Frequent publication sites include:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Mathematics of Operations Research

Some of their recent papers include:

  • What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation (2020), published in arXiv (Cornell University)
  • Individual Privacy Accounting via a Renyi Filter (2020), published in arXiv (Cornell University)

Other notable recent works published in collaboration or in closely related fields include:

  • Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation (2020), published in arXiv (Cornell University)
  • Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses (2020), published in arXiv (Cornell University)
  • Information-Theoretic Single-Server PIR in the Shuffle Model (2024), published in Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Vitaly Feldman frequently collaborates with several co-authors, including:

  • Kunal Talwar
  • Audra McMillan
  • Hilal Asi
  • Tomer Koren
  • Junye Chen

Best Publications

  • The reusable holdout: Preserving validity in adaptive data analysis

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

  • Preserving Statistical Validity in Adaptive Data Analysis

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

  • Cognitive computing building block: A versatile and efficient digital neuron model for neurosynaptic cores

    Andrew S. Cassidy;Paul Merolla;John V. Arthur;Steve K. Esser

  • Statistical Algorithms and a Lower Bound for Detecting Planted Cliques

    Vitaly Feldman;Elena Grigorescu;Lev Reyzin;Santosh S. Vempala

  • Does learning require memorization? a short tale about a long tail

    Vitaly Feldman

  • New Results for Learning Noisy Parities and Halfspaces

    V. Feldman;P. Gopalan;S. Khot;A.K. Ponnuswami

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

    Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan

  • Generalization in adaptive data analysis and holdout reuse

    Cynthia Dwork;Vitaly Feldman;Moritz Hardt;Toniann Pitassi

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

    Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan

  • What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation

    Vitaly Feldman;Chiyuan Zhang

  • Statistical algorithms and a lower bound for detecting planted cliques

    Vitaly Feldman;Elena Grigorescu;Lev Reyzin;Santosh Vempala

  • Agnostic Learning of Monomials by Halfspaces Is Hard

    Vitaly Feldman;Venkatesan Guruswami;Prasad Raghavendra;Yi Wu

  • Privacy Amplification by Iteration

    Vitaly Feldman;Ilya Mironov;Kunal Talwar;Abhradeep Thakurta

  • On using extended statistical queries to avoid membership queries

    Nader H. Bshouty;Vitaly Feldman

  • ON AGNOSTIC LEARNING OF PARITIES, MONOMIALS, AND HALFSPACES

    Vitaly Feldman;Parikshit Gopalan;Subhash Khot;Ashok Kumar Ponnuswami

  • Private Stochastic Convex Optimization with Optimal Rates

    Raef Bassily;Vitaly Feldman;Kunal Talwar;Abhradeep Guha Thakurta

  • High probability generalization bounds for uniformly stable algorithms with nearly optimal rate

    Vitaly Feldman;Jan Vondrak

  • Private stochastic convex optimization: optimal rates in linear time

    Vitaly Feldman;Tomer Koren;Kunal Talwar

  • Evolvability from learning algorithms

    Vitaly Feldman

  • On the Complexity of Random Satisfiability Problems with Planted Solutions

    Vitaly Feldman;Will Perkins;Santosh Vempala

  • Encode, Shuffle, Analyze Privacy Revisited: Formalizations and Empirical Evaluation.

    Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan

  • Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses

    Raef Bassily;Vitaly Feldman;Cristóbal Guzmán;Kunal Talwar

Frequent Co-Authors

Santosh Vempala
Santosh Vempala Georgia Institute of Technology
Jan Vondrák
Jan Vondrák Stanford University
Kunal Talwar
Kunal Talwar Apple (United States)
Moritz Hardt
Moritz Hardt Max Planck Institute for Intelligent Systems
Cynthia Dwork
Cynthia Dwork Harvard University
Toniann Pitassi
Toniann Pitassi Columbia University
Rocco A. Servedio
Rocco A. Servedio Columbia University
Abhradeep Thakurta
Abhradeep Thakurta Google (United States)
Aaron Roth
Aaron Roth University of Pennsylvania
Omer Reingold
Omer Reingold Stanford University

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