World's Best Scientists 2026 revealed!
Russell Greiner

Russell Greiner

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Computer Science
Canada
2025

D-Index & Metrics

Computer Science

D-Index
68
Citations
31302
World Ranking
2030
National Ranking
75

Russell Greiner 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 Russell Greiner 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: 333 publications — 79th percentile

79% of scientists in this discipline score the same or lower.

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

Russell Greiner 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 Russell Greiner 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: 68 D-Index — 86th percentile

86% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Canada Leader Award
  • 2022 - Research.com Computer Science in Canada Leader Award

Overview

Russell Greiner is affiliated with the University of Alberta in Canada. Their research output concentrates primarily on medicine, with a significant focus on molecular biology, artificial intelligence, radiology, nuclear medicine, imaging, cardiology, cardiovascular medicine, and epidemiology.

The scientist's work encompasses several main research topics including machine learning in healthcare, COVID-19 diagnosis using AI, COVID-19 epidemiological studies, metabolomics and mass spectrometry studies, ECG monitoring and analysis, data-driven disease surveillance, and computational drug discovery methods.

Frequent coauthors collaborating with Russell Greiner include Andrew J. Greenshaw, Sunil V. Kalmady, Bo Cao, David S. Wishart, and Padma Kaul.

The most common venues for publication are:

  • arXiv (Cornell University)
  • Scientific Reports
  • bioRxiv (Cold Spring Harbor Laboratory)
  • PLoS ONE
  • Canadian Medical Association Journal

Recent papers authored or coauthored by Russell Greiner cover diverse topics related to metabolomics, machine learning, and chemical data analysis. Notable publications include:

  • HMDB 5.0: the Human Metabolome Database for 2022, 2021, published in Nucleic Acids Research
  • CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification, 2021, published in Analytical Chemistry
  • BioTransformer 3.0-a web server for accurately predicting metabolic transformation products, 2022, published in Nucleic Acids Research
  • Implementing machine learning in medicine, 2021, published in Canadian Medical Association Journal
  • CFM-ID 4.0 - a web server for accurate MS-based metabolite identification, 2022, published in Nucleic Acids Research

Best Publications

  • HMDB: The human metabolome database

    David S. Wishart;Dan Tzur;Craig Knox;Roman Eisner

  • HMDB 3.0—The Human Metabolome Database in 2013

    David S. Wishart;Timothy Jewison;Anchi Guo;Michael Wilson

  • HMDB: a knowledgebase for the human metabolome

    David S. Wishart;Craig Knox;Anchi Guo;Roman Eisner

  • The Human Serum Metabolome

    Nikolaos Psychogios;David D. Hau;Jun Peng;An Chi Guo

  • ClassyFire: automated chemical classification with a comprehensive, computable taxonomy

    Yannick Djoumbou Feunang;Roman Eisner;Craig Knox;Leonid Chepelev

  • Learning Bayesian networks from data: an information-theory based approach

    Jie Cheng;Russell Greiner;Jonathan Kelly;David Bell

  • Comparing Bayesian network classifiers

    Jie Cheng;Russell Greiner

  • CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra

    Felicity Allen;Allison Pon;Michael Wilson;Russell Greiner

  • A correction to the algorithm in Reiter's theory of diagnosis

    Russell Greiner;Barbara A. Smith;Ralph W. Wilkerson

  • Competitive fragmentation modeling of ESI-MS/MS spectra for putative metabolite identification

    Felicity Allen;Russell Greiner;David S. Wishart

  • Predicting subcellular localization of proteins using machine-learned classifiers

    Z. Lu;D. Szafron;R. Greiner;P. Lu

  • BioTransformer: a comprehensive computational tool for small molecule metabolism prediction and metabolite identification.

    Yannick Djoumbou-Feunang;Jarlei Fiamoncini;Jarlei Fiamoncini;Alberto Gil-de-la-Fuente;Russell Greiner

  • Investigations of the effects of gender, diurnal variation, and age in human urinary metabolomic profiles.

    Carolyn M. Slupsky;Kathryn N. Rankin;James Wagner;Hao Fu

  • Learning Bayesian Belief Network Classifiers: Algorithms and System

    Jie Cheng;Russell Greiner

  • BASys: a web server for automated bacterial genome annotation.

    Gary H. Van Domselaar;Paul Stothard;Savita Shrivastava;Joseph A. Cruz

  • CFM-ID 4.0: More Accurate ESI-MS/MS Spectral Prediction and Compound Identification.

    Fei Wang;Jaanus Liigand;Jaanus Liigand;Siyang Tian;David Arndt

  • Accurate, fully-automated NMR spectral profiling for metabolomics.

    Siamak Ravanbakhsh;Philip Liu;Trent C. Bjordahl;Rupasri Mandal

  • Structural Extension to Logistic Regression: Discriminative Parameter Learning of Belief Net Classifiers

    Russell Greiner;Xiaoyuan Su;Bin Shen;Wei Zhou

  • Learning cost-sensitive active classifiers

    Russell Greiner;Adam J. Grove;Dan Roth

  • Learning by understanding analogies

    Russell Greiner

Frequent Co-Authors

David S. Wishart
David S. Wishart University of Alberta
Dale Schuurmans
Dale Schuurmans University of Alberta
Tingshao Zhu
Tingshao Zhu University of Chinese Academy of Sciences
Gerald Häubl
Gerald Häubl University of Alberta
Duane Szafron
Duane Szafron University of Alberta
Lihong Li
Lihong Li Amazon (United States)
Xin-Min Li
Xin-Min Li University of Alberta
John R. Mackey
John R. Mackey University of Alberta
Mark Schmidt
Mark Schmidt University of British Columbia
Vickie E. Baracos
Vickie E. Baracos University of Alberta

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