World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
12008
World Ranking
4091
National Ranking
92

Florent Krzakala 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 Florent Krzakala 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: 202 publications — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Florent Krzakala 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 Florent Krzakala 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: 56 D-Index — 72nd percentile

72% of scientists in this discipline score the same or lower.

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

Overview

Florent Krzakala is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research contributions focus primarily within the field of Computer Science, with a strong emphasis on Artificial Intelligence and associated subfields.

Their main areas of study include:

  • Artificial Intelligence
  • Statistics and Probability
  • Computational Mechanics
  • Statistical and Nonlinear Physics
  • Signal Processing

Key topics explored in their work encompass:

  • Neural Networks and Applications
  • Sparse and Compressive Sensing Techniques
  • Statistical Methods and Inference
  • Gaussian Processes and Bayesian Inference
  • Stochastic Gradient Optimization Techniques
  • Blind Source Separation Techniques
  • Statistical Mechanics and Entropy

Florent Krzakala has authored numerous academic papers, with notable examples including:

  • "Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction," 2020, Physical Review X
  • "Generalisation error in learning with random features and the hidden manifold model*," 2021, Journal of Statistical Mechanics Theory and Experiment
  • "Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime," 2020, arXiv (Cornell University)
  • "Learning curves of generic features maps for realistic datasets with a teacher-student model*," 2022, Journal of Statistical Mechanics Theory and Experiment

These papers span research on learning models, statistical mechanics, and system prediction within computational and theoretical frameworks.

Frequent co-authors collaborating with Florent Krzakala include:

  • Lenka Zdeborová
  • Bruno Loureiro
  • Hugo Cui
  • Cédric Gerbelot
  • Ludovic Stephan

The majority of their publications appear in:

  • arXiv (Cornell University)
  • Journal of Statistical Mechanics Theory and Experiment
  • IEEE Transactions on Information Theory
  • Proceedings of the National Academy of Sciences
  • HAL (Le Centre pour la Communication Scientifique Directe)

Florent Krzakala's research encompasses a blend of theoretical and applied methods across artificial intelligence, statistical physics, and computational sciences. Their publication record demonstrates a continued engagement with topics that bridge statistical inference techniques and neural network applications, offering insights within a computational mechanics context.

Best Publications

  • Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications.

    Aurelien Decelle;Florent Krzakala;Cristopher Moore;Lenka Zdeborová

  • Spectral redemption in clustering sparse networks

    Florent Krzakala;Cristopher Moore;Elchanan Mossel;Joseph Neeman

  • Gibbs states and the set of solutions of random constraint satisfaction problems

    Florent Krzakała;Andrea Montanari;Federico Ricci-Tersenghi;Guilhem Semerjian

  • Statistical physics of inference: thresholds and algorithms

    Lenka Zdeborová;Florent Krzakala

  • Inference and phase transitions in the detection of modules in sparse networks.

    Aurelien Decelle;Florent Krzakala;Cristopher Moore;Lenka Zdeborová

  • Statistical-Physics-Based Reconstruction in Compressed Sensing

    Florent Krzakala;Marc Mézard;François Sausset;Yifan Sun;Yifan Sun

  • Probabilistic reconstruction in compressed sensing: algorithms, phase diagrams, and threshold achieving matrices

    Florent Krzakala;Marc Mézard;Francois Sausset;Yifan Sun;Yifan Sun

  • Phase transitions in the coloring of random graphs

    Lenka Zdeborová;Florent Krzakala

  • Reference-less measurement of the transmission matrix of a highly scattering material using a DMD and phase retrieval techniques

    Angélique Drémeau;Antoine Liutkus;David Martina;Ori Katz

  • Optimal errors and phase transitions in high-dimensional generalized linear models

    Jean Barbier;Florent Krzakala;Nicolas Macris;Léo Miolane

  • The quantum adiabatic algorithm applied to random optimization problems: The quantum spin glass perspective

    Victor Bapst;Laura Foini;Florent Krzakala;Guilhem Semerjian

  • Mutual information for symmetric rank-one matrix estimation: A proof of the replica formula

    jean barbier;Mohamad Dia;Nicolas Macris;Florent Krzakala

  • Landscape analysis of constraint satisfaction problems.

    Florent Krzakala;Jorge Kurchan

  • Adaptive damping and mean removal for the generalized approximate message passing algorithm

    Jeremy Vila;Philip Schniter;Sundeep Rangan;Florent Krzakala

  • Large-Scale Optical Reservoir Computing for Spatiotemporal Chaotic Systems Prediction

    Mushegh Rafayelyan;Jonathan Dong;Yongqi Tan;Florent Krzakala

  • Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications

    Thibault Lesieur;Florent Krzakala;Florent Krzakala;Lenka Zdeborová

  • Entropy and mutual information in models of deep neural networks

    Marylou Gabrié;Andre Manoel;Clément Luneau;Jean Barbier

  • Hiding Quiet Solutions in Random Constraint Satisfaction Problems

    Florent Krzakala;Florent Krzakala;Lenka Zdeborová

  • Spectral Clustering of graphs with the Bethe Hessian

    Alaa Saade;Florent Krzakala;Lenka Zdeborova

  • Statistical and computational phase transitions in spiked tensor estimation

    Thibault Lesieur;Leo Miolane;Marc Lelarge;Florent Krzakala

  • Random projections through multiple optical scattering: Approximating Kernels at the speed of light

    A. Saade;F. Caltagirone;I. Carron;L. Daudet

  • Modelling the influence of data structure on learning in neural networks: the hidden manifold model

    Sebastian Goldt;Marc Mézard;Florent Krzakala;Lenka Zdeborová

Frequent Co-Authors

Lenka Zdeborová
Lenka Zdeborová École Polytechnique Fédérale de Lausanne
Laurent Daudet
Laurent Daudet Université Paris Cité
Marc Lelarge
Marc Lelarge École Normale Supérieure
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Yue M. Lu
Yue M. Lu Beijing University of Posts and Telecommunications
Cristopher Moore
Cristopher Moore Santa Fe Institute
Giorgio Parisi
Giorgio Parisi Sapienza University of Rome
Pasquale Calabrese
Pasquale Calabrese International School for Advanced Studies
Philip Schniter
Philip Schniter The Ohio State University
Sundeep Rangan
Sundeep Rangan New York University

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