World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
17313
World Ranking
5486
National Ranking
114

Marc P. C. Fossorier 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 Marc P. C. Fossorier 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: 279 publications — 69th percentile

69% of scientists in this discipline score the same or lower.

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

Marc P. C. Fossorier 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 Marc P. C. Fossorier 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: 50 D-Index — 62nd percentile

62% 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

  • 2006 - IEEE Fellow For contributions to coding and decoding methods.

Overview

What is he best known for?

The fields of study he is best known for:

  • Algorithm
  • Statistics
  • Algebra

His scientific interests lie mostly in Algorithm, Decoding methods, Low-density parity-check code, Sequential decoding and List decoding. His study looks at the intersection of Algorithm and topics like Theoretical computer science with Additive white Gaussian noise. The Decoding methods study combines topics in areas such as Computational complexity theory and Iterative method.

His research integrates issues of Binary code, Binary number, Belief propagation, Parity bit and Error detection and correction in his study of Low-density parity-check code. He focuses mostly in the field of Sequential decoding, narrowing it down to topics relating to Viterbi decoder and, in certain cases, Convolutional code. His study in List decoding is interdisciplinary in nature, drawing from both Berlekamp–Welch algorithm and Error floor.

His most cited work include:

  • Low-density parity-check codes based on finite geometries: a rediscovery and new results (1241 citations)
  • Reduced complexity iterative decoding of low-density parity check codes based on belief propagation (831 citations)
  • Reduced-complexity decoding of LDPC codes (802 citations)

What are the main themes of his work throughout his whole career to date?

Algorithm, Decoding methods, Low-density parity-check code, Block code and Linear code are his primary areas of study. His research investigates the connection between Algorithm and topics such as Theoretical computer science that intersect with problems in Coding gain. The Decoding methods study combines topics in areas such as Computational complexity theory, Additive white Gaussian noise, Code, Binary code and Upper and lower bounds.

His Low-density parity-check code research includes themes of Discrete mathematics, Binary erasure channel, Belief propagation and Binary number. In his study, Phase-shift keying is inextricably linked to Communication channel, which falls within the broad field of Block code. His biological study spans a wide range of topics, including List decoding and Parity bit.

He most often published in these fields:

  • Algorithm (61.84%)
  • Decoding methods (53.95%)
  • Low-density parity-check code (39.91%)

What were the highlights of his more recent work (between 2007-2019)?

  • Low-density parity-check code (39.91%)
  • Discrete mathematics (31.14%)
  • Algorithm (61.84%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Low-density parity-check code, Discrete mathematics, Algorithm, Decoding methods and Block code. The various areas that Marc P. C. Fossorier examines in his Low-density parity-check code study include Binary erasure channel, Turbo code and Binary number. The concepts of his Discrete mathematics study are interwoven with issues in Upper and lower bounds, Parity bit, Linear code and Combinatorics.

His Algorithm research incorporates elements of Additive white Gaussian noise and Theoretical computer science. His work carried out in the field of Decoding methods brings together such families of science as Binary code and Error detection and correction. His study looks at the relationship between Block code and topics such as Type, which overlap with Code word.

Between 2007 and 2019, his most popular works were:

  • Design of regular (2,d/sub c/)-LDPC codes over GF(q) using their binary images (275 citations)
  • Low-complexity decoding for non-binary LDPC codes in high order fields (160 citations)
  • Generalized and Doubly Generalized LDPC Codes With Random Component Codes for the Binary Erasure Channel (44 citations)

In his most recent research, the most cited papers focused on:

  • Algorithm
  • Statistics
  • Algebra

The scientist’s investigation covers issues in Low-density parity-check code, Discrete mathematics, Algorithm, Decoding methods and Error detection and correction. His Error floor study in the realm of Low-density parity-check code interacts with subjects such as Process. His Discrete mathematics study incorporates themes from Block code, Combinatorics and Parity bit.

His work on Linear code and Channel code as part of general Algorithm study is frequently linked to GRASP and Field, therefore connecting diverse disciplines of science. His Linear code research incorporates themes from Probabilistic logic, Turbo code and Concatenated error correction code. His study in the field of Hamming weight and List decoding is also linked to topics like Noise measurement.

Best Publications

  • Low-density parity-check codes based on finite geometries: a rediscovery and new results

    Y. Kou;S. Lin;M.P.C. Fossorier

  • Reduced complexity iterative decoding of low-density parity check codes based on belief propagation

    M.P.C. Fossorier;M. Mihaljevic;H. Imai

  • Reduced-complexity decoding of LDPC codes

    Jinghu Chen;A. Dholakia;E. Eleftheriou;M.P.C. Fossorier

  • Near optimum universal belief propagation based decoding of low-density parity check codes

    Jinghu Chen;M.P.C. Fossorier

  • Soft decision decoding of linear block codes based on ordered statistics

    M.P.C. Fossorier;Shu Lin

  • Decoding Algorithms for Nonbinary LDPC Codes Over GF $(q)$

    D. Declercq;M. Fossorier

  • Density evolution for two improved BP-Based decoding algorithms of LDPC codes

    J. Chen;M.P.C. Fossorier

  • Two simple stopping criteria for turbo decoding

    R.Y. Shao;Shu Lin;M.P.C. Fossorier

  • Shuffled iterative decoding

    Juntan Zhang;M.P.C. Fossorier

  • Applied Algebra, Algebraic Algorithms and Error-Correcting Codes

    Marc Fossorier;Tom Høholdt;Alain Poli

  • Design of regular (2,d/sub c/)-LDPC codes over GF(q) using their binary images

    C. Poulliat;M. Fossorier;D. Declercq

  • A modified weighted bit-flipping decoding of low-density Parity-check codes

    Juntan Zhang;M.P.C. Fossorier

  • Low-complexity decoding for non-binary LDPC codes in high order fields

    Adrian Voicila;David Declercq;Francois Verdier;Marc Fossorier

  • On the equivalence between SOVA and max-log-MAP decodings

    M.P.C. Fossorier;F. Burkert;Shu Lin;J. Hagenauer

  • Iterative reliability-based decoding of low-density parity check codes

    M.P.C. Fossorier

  • Iterative decoding of one-step majority logic deductible codes based on belief propagation

    R. Lucas;M.P.C. Fossorier;Yu Kou;Shu Lin

  • On the computation of the minimum distance of low-density parity-check codes

    Xiao-Yu Hu;M.P.C. Fossorier;E. Eleftheriou

  • Box and match techniques applied to soft-decision decoding

    A. Valembois;M. Fossorier

  • Two decoding algorithms for tailbiting codes

    R.Y. Shao;Shu Lin;M.P.C. Fossorier

  • Fast correlation attack algorithm with list decoding and an application

    Miodrag J. Mihaljevic;Marc P. C. Fossorier;Hideki Imai

  • Quasi-Cyclic Low-Density Parity-Check Codes From

    Marc P. C. Fossorier

  • Comment on "Quasi-Cyclic Low Density Parity Check Codes From Circulant Permutation Matrices"

    M. Hagiwara;M. Fossorier

Frequent Co-Authors

Shu Lin
Shu Lin University of California, Davis
Hideki Imai
Hideki Imai Chuo University
Marco Chiani
Marco Chiani University of Bologna
David Declercq
David Declercq CY Cergy Paris University
Tadao Kasami
Tadao Kasami Nara Institute of Science and Technology
Aleksandar Kavcic
Aleksandar Kavcic University of Hawaii at Manoa
Zixiang Xiong
Zixiang Xiong Texas A&M University
Desmond P. Taylor
Desmond P. Taylor University of Canterbury
Zhi Ding
Zhi Ding University of California, Davis

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