World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
10411
World Ranking
11436
National Ranking
4698

David Molnar 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 David Molnar 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: 85 publications — 4th percentile

4% of scientists in this discipline score the same or lower.

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

David Molnar 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 David Molnar 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: 35 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

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

Overview

David Molnar is affiliated with Microsoft in the United States and conducts research largely within the domain of social sciences. Their work spans several interconnected fields including political science and international relations, artificial intelligence, sociology and political science, geography, planning and development, as well as anthropology.

Their research touches on various topics such as Central European and Russian historical studies, historical geopolitical and social dynamics, privacy-preserving technologies in data, privacy, security and data protection, cryptography and data security, historical influence and diplomacy, and Hungarian social, economic, and educational studies.

Molnar has contributed to academic literature through several papers published in a range of venues. Recent publications include:

  • CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models, 2024, arXiv (Cornell University)
  • CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models, 2024, arXiv (Cornell University)
  • FILEFALVI FILICZKI JÁNOS ALBUM AMICORUMÁNAK MAGYAR VONATKOZÁSÚ BEJEGYZÉSEI, 2021, Gerundium
  • Klikk-keresési módszer alkalmazása az MTMT adatbázisban, 2020, Multidiszciplináris Tudományok
  • Az első magyarországi képvers? Filefalvi Filiczki János három képverséről, 2022, Magyar Könyvszemle

Their work has been published most frequently in:

  • arXiv (Cornell University)
  • Az Eszterházy Károly Katolikus Egyetem Történelemtudományi Doktori Iskolájának kiadványai. Konferenciák, műhelybeszélgetések
  • Gerundium
  • Multidiszciplináris Tudományok
  • Magyar Könyvszemle

David Molnar collaborates regularly with a number of coauthors, including:

  • Sahana Chennabasappa
  • Cyrus Nikolaidis
  • Daniel S. Song
  • Shengye Wan
  • Spencer Whitman

Best Publications

  • Automated Whitebox Fuzz Testing.

    Patrice Godefroid;Michael Y. Levin;David A. Molnar

  • Privacy and security in library RFID: issues, practices, and architectures

    David Molnar;David Wagner

  • SAGE: whitebox fuzzing for security testing

    Patrice Godefroid;Michael Y. Levin;David Molnar

  • The free haven project: distributed anonymous storage service

    Roger Dingledine;Michael J. Freedman;David Molnar

  • Homomorphic Signature Schemes

    Robert Johnson;David Molnar;Dawn Xiaodong Song;David Wagner

  • Security and Privacy Issues in E-passports

    A. Juels;D. Molnar;D. Wagner

  • A scalable, delegatable pseudonym protocol enabling ownership transfer of RFID tags

    David Molnar;Andrea Soppera;David Wagner

  • Enabling security in cloud storage SLAs with CloudProof

    Raluca Ada Popa;Jacob R. Lorch;David Molnar;Helen J. Wang

  • Security and privacy for augmented reality systems

    Franziska Roesner;Tadayoshi Kohno;David Molnar

  • Short chosen-prefix collisions for MD5 and the creation of a rogue CA certificate

    Marc Stevens;Alexander Sotirov;Jacob Appelbaum;Arjen K. Lenstra

  • Dynamic test generation to find integer bugs in x86 binary linux programs

    David Molnar;Xue Cong Li;David A. Wagner

  • The program counter security model: automatic detection and removal of control-flow side channel attacks

    David Molnar;Matt Piotrowski;David Schultz;David Wagner

  • Active property checking

    Patrice Godefroid;Michael Y. Levin;David A. Molnar

  • SAGE: Whitebox Fuzzing for Security Testing: SAGE has had a remarkable impact at Microsoft.

    Patrice Godefroid;Michael Y. Levin;David Molnar

  • Billions and billions of constraints: whitebox fuzz testing in production

    Ella Bounimova;Patrice Godefroid;David Molnar

  • MD5 considered harmful today, creating a rogue CA certificate

    A. Sotirov;M. Stevens;J. Appelbaum;Arjen K. Lenstra

  • Fast and precise sanitizer analysis with BEK

    Pieter Hooimeijer;Benjamin Livshits;David Molnar;Prateek Saxena

  • Symbolic finite state transducers: algorithms and applications

    Margus Veanes;Pieter Hooimeijer;Benjamin Livshits;David Molnar

  • SCRIPTGARD: automatic context-sensitive sanitization for large-scale legacy web applications

    Prateek Saxena;David Molnar;Benjamin Livshits

  • Why we can't be bothered to read privacy policies models of privacy economics as a lemons market

    Tony Vila;Rachel Greenstadt;David Molnar

  • The program counter security model : Automatic detection and removal of control-flow side channel attacks

    David Molnar;Matt Piotrowski;David Schultz;David Wagner

Frequent Co-Authors

Pál Sümegi
Pál Sümegi University of Szeged
Benjamin Livshits
Benjamin Livshits Imperial College London
Margus Veanes
Margus Veanes Microsoft (United States)
David Wagner
David Wagner University of California, Berkeley
Tadayoshi Kohno
Tadayoshi Kohno University of Washington
Franziska Roesner
Franziska Roesner University of Washington
Levente Vitos
Levente Vitos Royal Institute of Technology
Eyal Ofek
Eyal Ofek Microsoft (United States)
Helen J. Wang
Helen J. Wang Microsoft (United States)
Balazs Sumegi
Balazs Sumegi University of Pecs

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