World's Best Scientists 2026 revealed!
Daniel N. Rockmore

Daniel N. Rockmore

D-Index & Metrics

Engineering and Technology

D-Index
37
Citations
5083
World Ranking
8436
National Ranking
2337

Daniel N. Rockmore publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Daniel N. Rockmore sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 152 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Daniel N. Rockmore D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Daniel N. Rockmore sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 37 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Daniel N. Rockmore is affiliated with Dartmouth College in the United States. Their body of work spans multiple disciplines within social sciences, with a specific focus on law, artificial intelligence, sociology and political science, and general health professions.

The main fields of study for Rockmore include:

  • Social Sciences

The subfields of their research cover:

  • Law
  • General Health Professions
  • Artificial Intelligence
  • Sociology and Political Science
  • Political Science and International Relations

Rockmore's research topics reflect a concentration on judicial and constitutional studies, healthcare systems, legal and artificial intelligence intersections, and the interpretation of legal language. They have contributed significantly to topics such as:

  • Judicial and Constitutional Studies
  • Healthcare Systems and Technology
  • Artificial Intelligence in Law
  • Topic Modeling
  • Patient Satisfaction in Healthcare
  • Comparative and International Law Studies
  • Legal Language and Interpretation

Their recent publications include the following papers:

  • Legalbench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models (2023), published in SSRN Electronic Journal
  • The Problem of Data Bias in the Pool of Published U.S. Appellate Court Opinions (2020), published in Journal of Empirical Legal Studies
  • Modeling law search as prediction (2020), published in Artificial Intelligence and Law
  • Complementing human effort in online reviews: A deep learning approach to automatic content generation and review synthesis (2022), published in International Journal of Research in Marketing
  • LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models (2023), published in arXiv (Cornell University)

The frequent publication venues for Rockmore's work include:

  • SSRN Electronic Journal
  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Artificial Intelligence and Law
  • Journal of Empirical Legal Studies

Rockmore has collaborated extensively with other researchers. Their common coauthors are:

  • Michael A. Livermore
  • Keith Carlson
  • A. James O'Malley
  • Allen Riddell
  • Erika L. Moen

Best Publications

  • FFTs for the 2-Sphere-Improvements and Variations

    Dennis M. Healy;Daniel N. Rockmore;Sean S. B. Moore

  • Unbiased Metric Learning: On the Utilization of Multiple Datasets and Web Images for Softening Bias

    Chen Fang;Ye Xu;Daniel N. Rockmore

  • FFTs on the Rotation Group

    Peter J. Kostelec;Daniel N. Rockmore

  • A digital technique for art authentication

    Siwei Lyu;Daniel N. Rockmore;Hany Farid

  • Overlapping portfolios, contagion, and financial stability

    Fabio Caccioli;J. Doyne Farmer;J. Doyne Farmer;Nick Foti;Daniel Rockmore;Daniel Rockmore

  • Generalized FFTS - A Survey of Some Recent Results

    David K. Maslen;Daniel N. Rockmore

  • The Functional Magnetic Resonance Imaging Data Center (fMRIDC): the challenges and rewards of large-scale databasing of neuroimaging studies.

    John D. Van Horn;Jeffrey S. Grethe;Peter Kostelec;Jeffrey B. Woodward

  • 'We the Peoples': The Global Origins of Constitutional Preambles

    Tom Ginsburg;Nick J. Foti;Daniel Rockmore

  • Quantification of artistic style through sparse coding analysis in the drawings of Pieter Bruegel the Elder

    James M. Hughes;Daniel J. Graham;Daniel N. Rockmore;Daniel N. Rockmore

  • Fast Discrete Polynomial Transforms with Applications to Data Analysis for Distance Transitive Graphs

    J. R. Driscoll;D. M. Healy;D. N. Rockmore

  • The FFT: an algorithm the whole family can use

    D.N. Rockmore

  • Nonparametric sparsification of complex multiscale networks.

    Nicholas J. Foti;James M. Hughes;Daniel N. Rockmore;Daniel N. Rockmore

  • Sharing neuroimaging studies of human cognition.

    John Darrell Van Horn;Scott T Grafton;Daniel Rockmore;Michael S Gazzaniga

  • Efficient computation of the Fourier transform on finite groups

    Persi Diaconis;Daniel Rockmore

  • Generic quantum Fourier transforms

    Cristopher Moore;Daniel Rockmore;Alexander Russell

  • The power of basis selection in fourier sampling: hidden subgroup problems in affine groups

    Cristopher Moore;Daniel Rockmore;Alexander Russell;Leonard J. Schulman

  • Cyclic Renormalization and Automorphism Groups of Rooted Trees

    Hyman Bass;Maria Victoria Otero-Espinar;Daniel Rockmore;Charles Tresser

  • Separation of variables and the computation of Fourier transforms of finite groups, I

    David Maslen;David Maslen;Daniel Rockmore

  • A wreath product group approach to signal and image processing .I. Multiresolution analysis

    R. Foote;G. Mirchandani;D.N. Rockmore;D. Healy

  • Mapping the similarity space of paintings: Image statistics and visual perception

    Daniel J. Graham;Jay D. Friedenberg;Daniel N. Rockmore;David J. Field

  • Stability of the World Trade Web over time – An extinction analysis

    Nicholas J. Foti;Scott Pauls;Daniel N. Rockmore;Daniel N. Rockmore

  • A wreath product group approach to signal and image processing .II. Convolution, correlation, and applications

    G. Mirchandani;R. Foote;D.N. Rockmore;D. Healy

  • Some Applications of Generalized FFTs

    Daniel N Rockmore

Frequent Co-Authors

John Lafferty
John Lafferty Yale University
J. Doyne Farmer
J. Doyne Farmer University of Oxford
Cristopher Moore
Cristopher Moore Santa Fe Institute
Alexander Russell
Alexander Russell University of Connecticut
Gregory S. Chirikjian
Gregory S. Chirikjian University of Delaware
Yang Wang
Yang Wang Hong Kong University of Science and Technology
Tom Ginsburg
Tom Ginsburg University of Chicago
Michael S. Gazzaniga
Michael S. Gazzaniga University of California, Santa Barbara
John D. Van Horn
John D. Van Horn University of Virginia
Peter F. Stadler
Peter F. Stadler Leipzig University

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