World's Best Scientists 2026 revealed!

D-Index & Metrics

Chemistry

D-Index
93
Citations
26932
World Ranking
1822
National Ranking
674

Peter W. Carr publication distribution in Chemistry in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Chemistry in 2026. The highlighted bar marks where Peter W. Carr sits on this spectrum.

61–80 publications: 66 scientists 81–100 publications: 302 scientists 101–120 publications: 623 scientists 121–140 publications: 918 scientists 141–160 publications: 1,218 scientists 161–180 publications: 1,350 scientists 181–200 publications: 1,344 scientists 201–220 publications: 1,281 scientists 221–240 publications: 1,216 scientists 241–260 publications: 1,100 scientists 261–280 publications: 979 scientists 281–300 publications: 939 scientists 301–320 publications: 764 scientists 321–340 publications: 643 scientists 341–360 publications: 628 scientists 361–380 publications: 522 scientists 381–400 publications: 459 scientists 401–420 publications: 397 scientists 421–440 publications: 327 scientists 441–460 publications: 270 scientists 461–480 publications: 265 scientists 481–500 publications: 252 scientists 501–520 publications: 201 scientists 521–540 publications: 185 scientists 541–560 publications: 148 scientists 561–580 publications: 148 scientists 581–600 publications: 132 scientists 601–620 publications: 114 scientists 621–640 publications: 104 scientists 641–660 publications: 91 scientists 661–680 publications: 92 scientists 681–700 publications: 73 scientists 701–720 publications: 57 scientists 721–740 publications: 54 scientists 741–760 publications: 67 scientists 761–780 publications: 45 scientists 781–800 publications: 46 scientists 801–820 publications: 39 scientists 821–840 publications: 32 scientists 841–860 publications: 36 scientists 861–880 publications: 29 scientists 881–900 publications: 26 scientists 901–920 publications: 24 scientists 921–940 publications: 14 scientists 941–960 publications: 23 scientists 961–980 publications: 28 scientists 981–1,000 publications: 15 scientists 1,001–1,020 publications: 29 scientists 1,021–1,040 publications: 12 scientists 1,041–1,060 publications: 19 scientists 1,061–1,080 publications: 12 scientists 1,081–1,100 publications: 6 scientists 1,101–1,120 publications: 8 scientists 1,121–1,140 publications: 12 scientists 1,141–1,160 publications: 5 scientists 1,161–1,180 publications: 6 scientists 1,181–1,200 publications: 14 scientists 1,201–1,220 publications: 7 scientists 1,221–1,240 publications: 2 scientists 1,241–1,260 publications: 6 scientists 1,261–1,280 publications: 4 scientists 1,281–1,294 publications: 6 scientists 1,295+ publications: 100 scientists
61 publications 1,295+

This scientist: 451 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,295 publications or more.

Peter W. Carr D-index placement in Chemistry in 2026

The chart shows the D-index (discipline H-index) distribution of Chemistry scientists ranked by Research.com in 2026. The highlighted bar marks where Peter W. Carr sits on this spectrum.

40–41 D-Index: 289 scientists 42–43 D-Index: 612 scientists 44–45 D-Index: 808 scientists 46–47 D-Index: 776 scientists 48–49 D-Index: 835 scientists 50–51 D-Index: 861 scientists 52–53 D-Index: 872 scientists 54–55 D-Index: 933 scientists 56–57 D-Index: 1,051 scientists 58–59 D-Index: 930 scientists 60–61 D-Index: 882 scientists 62–63 D-Index: 834 scientists 64–65 D-Index: 731 scientists 66–67 D-Index: 775 scientists 68–69 D-Index: 683 scientists 70–71 D-Index: 646 scientists 72–73 D-Index: 561 scientists 74–75 D-Index: 501 scientists 76–77 D-Index: 437 scientists 78–79 D-Index: 388 scientists 80–81 D-Index: 354 scientists 82–83 D-Index: 292 scientists 84–85 D-Index: 275 scientists 86–87 D-Index: 254 scientists 88–89 D-Index: 235 scientists 90–91 D-Index: 185 scientists 92–93 D-Index: 192 scientists 94–95 D-Index: 155 scientists 96–97 D-Index: 163 scientists 98–99 D-Index: 125 scientists 100–101 D-Index: 105 scientists 102–103 D-Index: 105 scientists 104–105 D-Index: 112 scientists 106–107 D-Index: 88 scientists 108–109 D-Index: 68 scientists 110–111 D-Index: 69 scientists 112–113 D-Index: 65 scientists 114–115 D-Index: 79 scientists 116–117 D-Index: 61 scientists 118–119 D-Index: 44 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 40 scientists 124–125 D-Index: 33 scientists 126–127 D-Index: 26 scientists 128–129 D-Index: 34 scientists 130–131 D-Index: 35 scientists 132–133 D-Index: 25 scientists 134–135 D-Index: 27 scientists 136–137 D-Index: 17 scientists 138–139 D-Index: 16 scientists 140–141 D-Index: 20 scientists 142–143 D-Index: 20 scientists 144–145 D-Index: 15 scientists 146–147 D-Index: 9 scientists 148–149 D-Index: 9 scientists 150–151 D-Index: 16 scientists 152–153 D-Index: 11 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 3 scientists 158 D-Index: 3 scientists 159+ D-Index: 98 scientists
40 D-Index 159+

This scientist: 93 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 159 D-Index or more.

Overview

Peter W. Carr is affiliated with the University of Minnesota in the United States. Their research spans multiple fields, primarily focusing on Computer Science as well as Biochemistry, Genetics, and Molecular Biology.

The scientist has contributed to several topics within their main fields of study. These topics include:

  • Anomaly Detection Techniques and Applications
  • Computational Drug Discovery Methods
  • Molecular Biology Techniques and Applications
  • Gene expression and cancer classification
  • Chromatin Remodeling and Cancer
  • Cancer Mechanisms and Therapy
  • Protein Degradation and Inhibitors

Their research also covers a variety of subfields such as Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Pathology and Forensic Medicine, and Economics and Econometrics.

Peter W. Carr's recent published papers include:

  • "Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting," 2023, arXiv (Cornell University)
  • "Characterizing Multi-Agent Team Behavior from Partial Team Tracings: Evidence from the English Premier League," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Artificial intelligence platform, RADR®, aids in the discovery of DNA damaging agent for the ultra-rare cancer Atypical Teratoid Rhabdoid Tumors," 2022, Frontiers in Drug Discovery
  • "A machine learning-based gene signature of response to the novel alkylating agent LP-184 distinguishes its potential tumor indications," 2021, BMC Bioinformatics

Frequent co-authors in their collaborations include Umesh Kathad, Aditya Kulkarni, Joseph McDermott, Neha Biyani, and Kishor Bhatia, each collaborating on multiple occasions.

Peter W. Carr has published across a variety of venues, with contributions in:

  • BMC Bioinformatics
  • Frontiers in Drug Discovery
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • arXiv (Cornell University)

Best Publications

  • The chemical interpretation and practice of linear solvation energy relationships in chromatography

    Mark Vitha;Peter W. Carr

  • Chemistry of zirconia and its use in chromatography

    J Nawrocki;M P Rigney;A McCormick;P W Carr

  • Immobilized enzymes in analytical and clinical chemistry

    Peter W. Carr;Larry D. Bowers

  • Fast, comprehensive two-dimensional liquid chromatography.

    Dwight R. Stoll;Xiaoping Li;Xiaoli Wang;Peter W. Carr

  • The hydrophobic-subtraction model of reversed-phase column selectivity.

    L.R. Snyder;J.W. Dolan;P.W. Carr

  • Part II. Chromatography using ultra-stable metal oxide-based stationary phases for HPLC.

    J. Nawrocki;C. Dunlap;A. McCormick;P.W. Carr

  • Two-Dimensional Liquid Chromatography: A State of the Art Tutorial

    Dwight R. Stoll;Peter W. Carr

  • Study of retention processes in reversed-phase high-performance liquid chromatography by the use of the solvatochromic comparison method.

    Paul C. Sadek;Peter W. Carr;Ruth M. Doherty;Mortimer J. Kamlet

  • Column selectivity in reversed-phase liquid chromatography. I. A general quantitative relationship

    N. S. Wilson;M. D. Nelson;J. W. Dolan;L. R. Snyder

  • Accuracy of empirical correlations for estimating diffusion coefficients in aqueous organic mixtures.

    Jianwei Li;Peter W. Carr

  • Part I. Chromatography using ultra-stable metal oxide-based stationary phases for HPLC

    Unknown

  • High-temperature ultrafast liquid chromatography.

    Bingwen Yan;Jianhong Zhao;James S. Brown;John Blackwell

  • Study of retention in reversed-phase liquid chromatography using linear solvation energy relationships. I. The stationary phase

    Lay Choo Tan;Peter W. Carr;Michael H. Abraham

  • Fast, comprehensive online two-dimensional high performance liquid chromatography through the use of high temperature ultra-fast gradient elution reversed-phase liquid chromatography.

    Dwight R. Stoll;Jerry D. Cohen;Peter W. Carr

  • Study of temperature and mobile-phase effects in reversed-phase high-performance liquid chromatography by the use of the solvatochromic comparison method.

    Peter W. Carr;Ruth M. Doherty;Mortimer J. Kamlet;Robert W. Taft

  • Effect of first-dimension undersampling on effective peak capacity in comprehensive two-dimensional separations.

    Joe M. Davis;Dwight R. Stoll;Peter W. Carr

  • Equation for peak capacity estimation in two-dimensional liquid chromatography.

    Xiaoping Li;Dwight R. Stoll;Peter W. Carr

  • Fast, comprehensive two-dimensional HPLC separation of tryptic peptides based on high-temperature HPLC.

    Dwight R. Stoll;Peter W. Carr

  • Solvatochromism, Linear Solvation Energy Relationships, and Chromatography

    P.W. Carr

  • Column selectivity in reversed-phase liquid chromatography II. Effect of a change in conditions.

    N. S. Wilson;M. D. Nelson;J. W. Dolan;L. R. Snyder

  • Physical and chemical characterization of microporous zirconia

    M.P. Rigney;E.F. Funkenbusch;P.W. Carr

Frequent Co-Authors

Patrick Lucey
Patrick Lucey Stats Perform
Alon V. McCormick
Alon V. McCormick University of Minnesota
Iain Matthews
Iain Matthews University of East Anglia
Yisong Yue
Yisong Yue California Institute of Technology
Lloyd R. Snyder
Lloyd R. Snyder University of Minnesota
Michael H. Abraham
Michael H. Abraham University College London
Sridha Sridharan
Sridha Sridharan Queensland University of Technology
Heather J. Koldewey
Heather J. Koldewey Zoological Society of London
Charles A. Eckert
Charles A. Eckert Georgia Institute of Technology
Richard Hartley
Richard Hartley Australian National University

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