World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
9156
World Ranking
7895
National Ranking
3409

Gerome Miklau 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 Gerome Miklau 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: 117 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Gerome Miklau 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 Gerome Miklau 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

Gerome Miklau is affiliated with the University of Massachusetts Amherst in the United States. Their research primarily focuses on computer science, with a distinct emphasis on artificial intelligence and privacy-preserving technologies in data.

The scientist's work spans several subfields including artificial intelligence, computer networks and communications, electrical and electronic engineering, epidemiology, and computer science applications. Their research intersects multiple topics such as privacy-preserving technologies in data, cryptography and data security, stochastic gradient optimization techniques, vehicular ad hoc networks (VANETs), mobile crowdsensing and crowdsourcing, privacy, security, and data protection, as well as data-driven disease surveillance.

Miklau's recent research publications include:

  • "Winning the NIST Contest: A scalable and general approach to differentially private synthetic data" (2021), Journal of Privacy and Confidentiality
  • "AIM" (2022), Proceedings of the VLDB Endowment
  • "Benchmarking Differentially Private Synthetic Data Generation Algorithms" (2021), arXiv (Cornell University)
  • "Investigating Visual Analysis of Differentially Private Data" (2020), IEEE Transactions on Visualization and Computer Graphics
  • "AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data" (2022), arXiv (Cornell University)

Frequent publication venues for Miklau's work include arXiv (Cornell University), the Journal of Privacy and Confidentiality, the Proceedings of the VLDB Endowment, IEEE Transactions on Visualization and Computer Graphics, and ACM Transactions on Database Systems.

Collaborative work is notable in Miklau's career. Frequent co-authors are Ashwin Machanavajjhala, Ryan McKenna, Michael Hay, Daniel Sheldon, and Sam Haney. These collaborations highlight an active engagement with peers in advancing topics related to data privacy and security.

Best Publications

  • Resisting structural re-identification in anonymized social networks

    Michael Hay;Gerome Miklau;David Jensen;Don Towsley

  • Boosting the accuracy of differentially private histograms through consistency

    Michael Hay;Vibhor Rastogi;Gerome Miklau;Dan Suciu

  • Anonymizing Social Networks

    Michael Hay;Gerome Miklau;David Jensen;Philipp Weis

  • Accurate Estimation of the Degree Distribution of Private Networks

    Michael Hay;Chao Li;Gerome Miklau;David Jensen

  • Optimizing linear counting queries under differential privacy

    Chao Li;Michael Hay;Vibhor Rastogi;Gerome Miklau

  • Controlling access to published data using cryptography

    Gerome Miklau;Dan Suciu

  • Containment and equivalence for a fragment of XPath

    Gerome Miklau;Dan Suciu

  • Containment and equivalence for an XPath fragment

    Gerome Miklau;Dan Suciu

  • Processing XML Streams with Deterministic Automata

    Todd J. Green;Gerome Miklau;Makoto Onizuka;Dan Suciu

  • A formal analysis of information disclosure in data exchange

    Gerome Miklau;Dan Suciu

  • Processing XML streams with deterministic automata and stream indexes

    Todd J. Green;Ashish Gupta;Gerome Miklau;Makoto Onizuka

  • The Piazza peer data management project

    Igor Tatarinov;Zachary Ives;Jayant Madhavan;Alon Halevy

  • A formal analysis of information disclosure in data exchange

    Gerome Miklau;Dan Suciu

  • A Theory of Pricing Private Data

    Chao Li;Daniel Yang Li;Gerome Miklau;Dan Suciu

  • A data- and workload-aware algorithm for range queries under differential privacy

    Chao Li;Michael Hay;Gerome Miklau;Yue Wang

  • Relationship privacy: output perturbation for queries with joins

    Vibhor Rastogi;Michael Hay;Gerome Miklau;Dan Suciu

  • A theory of pricing private data

    Chao Li;Daniel Yang Li;Gerome Miklau;Dan Suciu

  • Principled Evaluation of Differentially Private Algorithms using DPBench

    Michael Hay;Ashwin Machanavajjhala;Gerome Miklau;Yan Chen

  • Differential privacy in data publication and analysis

    Yin Yang;Zhenjie Zhang;Gerome Miklau;Marianne Winslett

  • An adaptive mechanism for accurate query answering under differential privacy

    Chao Li;Gerome Miklau

  • The matrix mechanism: optimizing linear counting queries under differential privacy

    Chao Li;Gerome Miklau;Michael Hay;Andrew Mcgregor

Frequent Co-Authors

Dan Suciu
Dan Suciu University of Washington
Ashwin Machanavajjhala
Ashwin Machanavajjhala Duke University
Serge Abiteboul
Serge Abiteboul École Normale Supérieure
Hosagrahar V. Jagadish
Hosagrahar V. Jagadish University of Michigan–Ann Arbor
David Jensen
David Jensen University of Massachusetts Amherst
Andrew McCallum
Andrew McCallum University of Massachusetts Amherst
Brian Neil Levine
Brian Neil Levine University of Massachusetts Amherst
Bill Howe
Bill Howe University of Washington
Don Towsley
Don Towsley University of Massachusetts Amherst
Andrew McGregor
Andrew McGregor University of Massachusetts Amherst

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