World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
11888
World Ranking
6094
National Ranking
235

Matei Ripeanu 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 Matei Ripeanu 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: 178 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Matei Ripeanu 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 Matei Ripeanu 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: 48 D-Index — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Overview

Matei Ripeanu is affiliated with the University of British Columbia in Canada. Their research spans several main fields of study including Computer Science and Biochemistry, Genetics and Molecular Biology. Within these fields, their subfields of focus include Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing, Molecular Biology, and Artificial Intelligence.

Their work has involved a variety of scientific topics, with notable emphasis on Graph Theory and Algorithms, Advanced Database Systems and Queries, Data Management and Algorithms, as well as Genomics and Phylogenetic Studies, Machine Learning in Bioinformatics, Chemical Synthesis and Analysis, and Energy Efficient Wireless Sensor Networks.

Among their recent publications are:

  • "The future is big graphs", 2021, Communications of the ACM
  • "The Future is Big Graphs! A Community View on Graph Processing Systems", 2020, Repository for Publications and Research Data (ETH Zurich)
  • "Scalable Pattern Matching in Metadata Graphs via Constraint Checking", 2021, ACM Transactions on Parallel Computing
  • "Maximum Flow on Highly Dynamic Graphs", 2023, arXiv (Cornell University)
  • "SSSP-Del: Fully Dynamic Distributed Algorithm for Single-Source Shortest Path", 2025, arXiv (Cornell University)

Frequent co-authors collaborating with Ripeanu include Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup, and Khaled Ammar.

Their research has been published in venues such as arXiv (Cornell University), Communications of the ACM, Repository for Publications and Research Data (ETH Zurich), and ACM Transactions on Parallel Computing.

Best Publications

  • Mapping the Gnutella network

    R. Matei;A. Iamnitchi;P. Foster

  • Peer-to-peer architecture case study: Gnutella network

    M. Ripeanu

  • Mapping the Gnutella Network: Properties of Large-Scale Peer-to-Peer Systems and Implications for System Design

    Matei Ripeanu;Ian T. Foster;Adriana Iamnitchi

  • The socialbot network: when bots socialize for fame and money

    Yazan Boshmaf;Ildar Muslukhov;Konstantin Beznosov;Matei Ripeanu

  • Amazon S3 for science grids: a viable solution?

    Mayur R. Palankar;Adriana Iamnitchi;Matei Ripeanu;Simson Garfinkel

  • Giggle: A Framework for Constructing Scalable Replica Location Services

    Ann Chervenak;Ewa Deelman;Ian Foster;Leanne Guy

  • Mapping the Gnutella Network: Macroscopic Properties of Large-Scale Peer-to-Peer Systems

    Matei Ripeanu;Ian T. Foster

  • Deconstructing the Kazaa network

    N. Leibowitz;M. Ripeanu;A. Wierzbicki

  • Design and analysis of a social botnet

    Yazan Boshmaf;Ildar Muslukhov;Konstantin Beznosov;Matei Ripeanu

  • Small-world file-sharing communities

    A. Iamnitchi;M. Ripeanu;I. Foster

  • Supporting Efficient Execution in Heterogeneous Distributed Computing Environments with Cactus and Globus

    Gabrielle Allen;Thomas Dramlitsch;Ian Foster;Nicholas T. Karonis

  • Influences on cooperation in BitTorrent communities

    Nazareno Andrade;Miranda Mowbray;Aliandro Lima;Gustavo Wagner

  • Locating Data in (Small-World?) Peer-to-Peer Scientific Collaborations

    Adriana Iamnitchi;Matei Ripeanu;Ian T. Foster

  • VMFlock: virtual machine co-migration for the cloud

    Samer Al-Kiswany;Dinesh Subhraveti;Prasenjit Sarkar;Matei Ripeanu

  • ‘To Share or not to Share’ An Analysis of Incentives to Contribute in Collaborative File Sharing Environments

    Kavitha Ranganathan;Matei Ripeanu;Ankur Sarin;Ian Foster

  • GPU-Qin: A methodology for evaluating the error resilience of GPGPU applications

    Bo Fang;Karthik Pattabiraman;Matei Ripeanu;Sudhanva Gurumurthi

  • Íntegro: Leveraging Victim Prediction for Robust Fake Account Detection in OSNs

    Yazan Boshmaf;Dionysios Logothetis;Georgos Siganos;Jorge Lería

  • The future is big graphs: a community view on graph processing systems

    Sherif Sakr;Angela Bonifati;Hannes Voigt;Alexandru Iosup

  • Cache replacement policies revisited: the case of P2P traffic

    A. Wierzbicki;N. Leibowitz;M. Ripeanu;R. Wozniak

  • A yoke of oxen and a thousand chickens for heavy lifting graph processing

    Abdullah Gharaibeh;Lauro Beltrao Costa;Elizeu Santos-Neto;Matei Ripeanu

  • A decentralized, adaptive replica location mechanism

    M. Ripeanu;I. Foster

Frequent Co-Authors

Ian Foster
Ian Foster University of Chicago
Adriana Iamnitchi
Adriana Iamnitchi Maastricht University
Konstantin Beznosov
Konstantin Beznosov University of British Columbia
Karthik Pattabiraman
Karthik Pattabiraman University of British Columbia
Daniel S. Katz
Daniel S. Katz University of Illinois at Urbana-Champaign
Michael Wilde
Michael Wilde Argonne National Laboratory
Ioan Raicu
Ioan Raicu Illinois Institute of Technology
Jussara M. Almeida
Jussara M. Almeida Universidade Federal de Minas Gerais
Alexandru Iosup
Alexandru Iosup Vrije Universiteit Amsterdam
Sudhanva Gurumurthi
Sudhanva Gurumurthi Advanced Micro Devices (United States)

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