World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
47579
World Ranking
2666
National Ranking
1323

Rick Stevens 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 Rick Stevens 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: 212 publications — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Rick Stevens 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 Rick Stevens 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: 63 D-Index — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Overview

Rick Stevens is affiliated with Argonne National Laboratory in the United States. Their research spans multiple fields, primarily within the domains of Biochemistry, Genetics and Molecular Biology, and Computer Science. Within these broader categories, Stevens has focused on key subfields including Molecular Biology, Computational Theory and Mathematics, Artificial Intelligence, Materials Chemistry, and Electrical and Electronic Engineering.

Their work frequently addresses topics such as Computational Drug Discovery Methods, Machine Learning in Materials Science, Protein Structure and Dynamics, Genomics and Phylogenetic Studies, Bioinformatics and Genomic Networks, Gene Expression and Cancer Classification, and Genetics, Bioinformatics, and Biomedical Research.

Stevens has contributed significantly to several scientific publications across diverse venues. Some of the frequent publication outlets are:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Scientific Reports
  • Briefings in Bioinformatics
  • Journal of Clinical Oncology

Among their notable recent papers are:

  • Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR, published in 2022 in Nucleic Acids Research
  • Converting tabular data into images for deep learning with convolutional neural networks, published in 2021 in Scientific Reports
  • Exascale applications: skin in the game, published in 2020 in Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences
  • Deep learning methods for drug response prediction in cancer: Predominant and emerging trends, published in 2023 in Frontiers in Medicine
  • Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence, published in 2022 in Matter

Stevens has collaborated extensively with several co-authors in their research output. Frequent collaborators include Thomas Brettin, Austin Clyde, Fangfang Xia, Maulik Shukla, and Alexander Partin.

Best Publications

  • The RAST Server: Rapid Annotations using Subsystems Technology

    Ramy K. Aziz;Ramy K. Aziz;Daniela Bartels;Aaron A. Best;Matthew DeJongh

  • The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST)

    Ross A. Overbeek;Robert Olson;Gordon D. Pusch;Gary J. Olsen

  • The Metagenomics RAST Server: A Public Resource for the Automatic Phylogenetic and Functional Analysis of Metagenomes

    Folker Meyer;Folker Meyer;Daniel Paarmann;Mark D'Souza;Robert Olson

  • RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes

    Thomas Brettin;Thomas Brettin;James J. Davis;James J. Davis;Terry Disz;Robert A. Edwards;Robert A. Edwards

  • A communal catalogue reveals Earth’s multiscale microbial diversity

    Luke R. Thompson;Luke R. Thompson;Luke R. Thompson;Jon G. Sanders;Daniel McDonald;Amnon Amir

  • The Subsystems Approach to Genome Annotation and its Use in the Project to Annotate 1000 Genomes

    Ross Overbeek;Tadhg P. Begley;Ralph M. Butler;Jomuna Choudhuri

  • Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

    Alice R. Wattam;James J. Davis;James J. Davis;Rida Assaf;Sébastien Boisvert

  • KBase: The United States Department of Energy Systems Biology Knowledgebase.

    Adam P. Arkin;Adam P. Arkin;Robert W. Cottingham;Christopher S. Henry;Nomi L. Harris

  • PATRIC, the bacterial bioinformatics database and analysis resource

    Alice R. Wattam;David Abraham;Oral Dalay;Terry Disz

  • High-throughput generation, optimization and analysis of genome-scale metabolic models

    Christopher S Henry;Matthew DeJongh;Aaron A Best;Paul M Frybarger

  • The International Exascale Software Project roadmap

    Jack Dongarra;Pete Beckman;Terry Moore;Patrick Aerts

  • The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities.

    James J. Davis;James J. Davis;Alice R. Wattam;Alice R. Wattam;Ramy K. Aziz;Thomas S. Brettin;Thomas S. Brettin

  • Portable Programs for Parallel Processors

    Ewing Lusk;James Boyle;Ralph Butler;Terrence Disz

  • The Aurora or-parallel Prolog system

    E. Lusk;R. Butler;T. Disz;R. Olson

  • Unlocking the potential of metagenomics through replicated experimental design

    Rob Knight;Janet Jansson;Janet Jansson;Dawn Field;Noah Fierer

  • Meeting Report: The Terabase Metagenomics Workshop and the Vision of an Earth Microbiome Project

    Jack A. Gilbert;Jack A. Gilbert;Folker Meyer;Dion Antonopoulos;Pavan Balaji

  • Overview of the I-Way: Wide-Area Visual Supercomputing

    Thomas A. Defanti;Ian Foster;Michael E. Papka;Rick Stevens

  • Using machine learning to predict antimicrobial MICs and associated genomic features for nontyphoidal Salmonella

    Marcus Nguyen;Marcus Nguyen;S. Wesley Long;S. Wesley Long;Patrick F. McDermott;Randall J. Olsen;Randall J. Olsen

  • Antimicrobial Resistance Prediction in PATRIC and RAST.

    James J. Davis;Sébastien Boisvert;Thomas Brettin;Thomas Brettin;Ronald W. Kenyon

  • Access grid: Immersive group-to-group collaborative visualization

    L. Childers;T. Disz;R. Olson;M. E. Papka

  • The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes.

    Florent E. Angly;Dana Willner;Alejandra Prieto-Davó;Robert A. Edwards;Robert A. Edwards

Frequent Co-Authors

Thomas Brettin
Thomas Brettin Argonne National Laboratory
Folker Meyer
Folker Meyer Argonne National Laboratory
Ian Foster
Ian Foster University of Chicago
Ross Overbeek
Ross Overbeek Argonne National Laboratory
Jack A. Gilbert
Jack A. Gilbert University of California, San Diego
Gary J. Olsen
Gary J. Olsen University of Illinois at Urbana-Champaign
Janet K. Jansson
Janet K. Jansson Pacific Northwest National Laboratory
Rob Knight
Rob Knight University of California, San Diego
Ramy K. Aziz
Ramy K. Aziz Cairo University
Shantenu Jha
Shantenu Jha Rutgers, The State University of New Jersey

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