World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5590
World Ranking
11651
National Ranking
46

Marta Mattoso 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 Marta Mattoso 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: 318 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

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

Marta Mattoso 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 Marta Mattoso 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

Marta Mattoso is affiliated with the Federal University of Rio de Janeiro in Brazil. Their research primarily spans the fields of computer science and decision sciences, with particular focus on subfields such as computer networks and communications, information systems and management, and molecular biology.

Their contributions cover a diverse range of topics in scientific computing and data management, distributed and parallel computing systems, research data management practices, advanced data storage technologies, machine learning in materials science, microbial community ecology and physiology, and genomics and phylogenetic studies.

Marta Mattoso has authored multiple papers published in several scientific venues. Some notable recent publications include:

  • A new genomic taxonomy system for the Synechococcus collective (2020) in Environmental Microbiology
  • Workflow provenance in the lifecycle of scientific machine learning (2021) in Concurrency and Computation Practice and Experience
  • Workflows Community Summit: Bringing the Scientific Workflows Community Together (2021) in arXiv (Cornell University)
  • Capturing and Analyzing Provenance from Spark-based Scientific Workflows with SAMbA-RaP (2020) in Future Generation Computer Systems
  • DfAnalyzer: Runtime dataflow analysis tool for Computational Science and Engineering applications (2020) in SoftwareX

Frequent venues of publication include:

  • arXiv (Cornell University)
  • SoftwareX
  • Journal of Information and Data Management
  • PeerJ Computer Science
  • Environmental Microbiology

Frequent collaborators include Daniel de Oliveira, Patrick Valduriez, Liliane Kunstmann, Débora Pina, and Vinícius Salazar. These collaborations have contributed to the multidisciplinary nature of their research outputs.

Best Publications

  • A Survey of Data-Intensive Scientific Workflow Management

    Ji Liu;Esther Pacitti;Patrick Valduriez;Marta Mattoso

  • Building reliable Web services compositions

    Paulo F. Pires;Mario R. F. Benevides;Marta Mattoso

  • SciCumulus: A Lightweight Cloud Middleware to Explore Many Task Computing Paradigm in Scientific Workflows

    Daniel de Oliveira;Eduardo Ogasawara;Fernanda Baião;Marta Mattoso

  • Adaptive Normalization: A novel data normalization approach for non-stationary time series

    Eduardo Ogasawara;Leonardo C. Martinez;Daniel de Oliveira;Geraldo Zimbrao

  • An algebraic approach for data-centric scientific workflows

    Eduardo Ogasawara;Jonas Dias;Daniel de Oliveira;Fábio Porto

  • Towards supporting the life cycle of large scale scientific experiments

    Marta Mattoso;Cláudia Werner;Guilherme Horta Travassos;Vanessa Braganholo

  • Towards a Taxonomy of Provenance in Scientific Workflow Management Systems

    Sérgio Manuel Serra da Cruz;Maria Luiza M. Campos;Marta Mattoso

  • A Provenance-based Adaptive Scheduling Heuristic for Parallel Scientific Workflows in Clouds

    Daniel Oliveira;Kary A. Ocaña;Fernanda Baião;Marta Mattoso

  • SciPhy: a cloud-based workflow for phylogenetic analysis of drug targets in protozoan genomes

    Kary A. C. S. Ocaña;Daniel de Oliveira;Eduardo Ogasawara;Alberto M. R. Dávila

  • Towards a Taxonomy for Cloud Computing from an e-Science Perspective

    Daniel de Oliveira;Fernanda Araujo Baião;Marta Mattoso

  • Chiron: a parallel engine for algebraic scientific workflows

    Eduardo S. Ogasawara;Eduardo S. Ogasawara;Jonas Dias;Vítor Silva;Fernando Seabra Chirigati

  • Capturing and querying workflow runtime provenance with PROV: a practical approach

    Flavio Costa;Vítor Silva;Daniel de Oliveira;Kary Ocaña

  • Odyssey: a reuse environment based on domain models

    R.M.M. Braga;C.M.L. Werner;M. Mattoso

  • Dynamic steering of HPC scientific workflows

    Marta Mattoso;Jonas Dias;Kary A.C.S. Ocaña;Eduardo Ogasawara

  • Managing structural genomic workflows using web services

    Maria Cláudia Cavalcanti;Rafael Targino;Fernanda Baião;Shaila C. Rössle

  • The use of mediation and ontology technologies for software component information retrieval

    Regina M. M. Braga;Marta Mattoso;Cláudia M. L. Werner

  • Grid Data Management: Open Problems and New Issues

    Esther Pacitti;Patrick Valduriez;Marta Mattoso

  • A Distribution Design Methodology for Object DBMS

    Fernanda Baião;Marta Mattoso;Gerson Zaverucha

  • An adaptive parallel execution strategy for cloud-based scientific workflows

    Daniel de Oliveira;Eduardo Ogasawara;Kary Ocaña;Fernanda Baião

  • Parallel OLAP query processing in database clusters with data replication

    Alexandre A. Lima;Camille Furtado;Patrick Valduriez;Marta Mattoso

Frequent Co-Authors

Patrick Valduriez
Patrick Valduriez French Institute for Research in Computer Science and Automation - INRIA
Michael Wilde
Michael Wilde Argonne National Laboratory
Ian Foster
Ian Foster University of Chicago
Fabiano L. Thompson
Fabiano L. Thompson Federal University of Rio de Janeiro
Ana Tereza Ribeiro de Vasconcelos
Ana Tereza Ribeiro de Vasconcelos National Laboratory of Scientific Computing
Eric J. Simon
Eric J. Simon New York University
Daniel S. Katz
Daniel S. Katz University of Illinois at Urbana-Champaign
Ewa Deelman
Ewa Deelman University of Southern California
Jean Swings
Jean Swings Ghent University
Karan Vahi
Karan Vahi University of Southern California

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