World's Best Scientists 2026 revealed!
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Computer Science
Switzerland
2025

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
65
Citations
30359
World Ranking
1178
National Ranking
28

Computer Science

D-Index
68
Citations
31793
World Ranking
2029
National Ranking
48

Pascal Frossard publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Pascal Frossard sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 512 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Pascal Frossard D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Pascal Frossard sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 65 D-Index — 83rd percentile

83% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Pascal Frossard is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research primarily spans the field of computer science, with a significant focus on artificial intelligence, computer vision and pattern recognition, statistical and nonlinear physics, molecular biology, and electrical and electronic engineering.

The scientist's work covers several advanced topics, including:

  • Adversarial Robustness in Machine Learning
  • Advanced Graph Neural Networks
  • Complex Network Analysis Techniques
  • Anomaly Detection Techniques and Applications
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Explainable Artificial Intelligence (XAI)

Frequent coauthors in Frossard's publications include:

  • Guillermo Ortiz-Jiménez
  • Apostolos Modas
  • Dorina Thanou
  • Seyed-Mohsen Moosavi-Dezfooli
  • Clément Vignac

Frossard's scholarly output is documented across several publication venues, with the largest number of works appearing in:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal and Information Processing over Networks
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Transactions on Multimedia
  • bioRxiv (Cold Spring Harbor Laboratory)

A selection of recent papers includes:

  • Graph Signal Processing for Machine Learning: A Review and New Perspectives (2020) published in IEEE Signal Processing Magazine
  • Equivariant 3D-conditional diffusion model for molecular linker design (2024) published in Nature Machine Intelligence
  • DiGress: Discrete Denoising diffusion for graph generation (2022) published on arXiv (Cornell University)
  • Interpretable temporal-spatial graph attention network for multi-site PV power forecasting (2022) published in Applied Energy
  • A Structured Dictionary Perspective on Implicit Neural Representations (2022) published at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scope of their research often intersects with advanced machine learning techniques applied to graph data, neural networks, and interpretable AI models. The interdisciplinary nature of their publication record reflects engagement in fields bridging artificial intelligence, signal processing, and applied machine learning methodologies.

Best Publications

  • DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks

    Seyed-Mohsen Moosavi-Dezfooli;Alhussein Fawzi;Pascal Frossard

  • The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains

    David I Shuman;Sunil K. Narang;Pascal Frossard;Antonio Ortega

  • Universal Adversarial Perturbations

    Seyed-Mohsen Moosavi-Dezfooli;Alhussein Fawzi;Omar Fawzi;Pascal Frossard

  • Graph Signal Processing: Overview, Challenges, and Applications

    Antonio Ortega;Pascal Frossard;Jelena Kovacevic;Jose M. F. Moura

  • Dictionary learning: What is the right representation for my signal?

    Ivana Tosic;Pascal Frossard

  • Dictionary Learning

    Ivana Tošić;Pascal Frossard

  • Learning Laplacian Matrix in Smooth Graph Signal Representations

    Xiaowen Dong;Dorina Thanou;Pascal Frossard;Pierre Vandergheynst

  • Learning Graphs From Data: A Signal Representation Perspective

    Xiaowen Dong;Dorina Thanou;Michael Rabbat;Pascal Frossard

  • Analysis of classifiers’ robustness to adversarial perturbations

    Alhussein Fawzi;Omar Fawzi;Pascal Frossard

  • Robustness of classifiers: from adversarial to random noise

    Alhussein Fawzi;Seyed-Mohsen Moosavi-Dezfooli;Pascal Frossard

  • Clustering on Multi-Layer Graphs via Subspace Analysis on Grassmann Manifolds

    Xiaowen Dong;Pascal Frossard;Pierre Vandergheynst;Nikolai Nefedov

  • Graph-Based Compression of Dynamic 3D Point Cloud Sequences

    Dorina Thanou;Philip A. Chou;Pascal Frossard

  • Adaptive data augmentation for image classification

    Alhussein Fawzi;Horst Samulowitz;Deepak Turaga;Pascal Frossard

  • Robustness via Curvature Regularization, and Vice Versa

    Seyed-Mohsen Moosavi-Dezfooli;Alhussein Fawzi;Jonathan Uesato;Pascal Frossard

  • The Robustness of Deep Networks: A Geometrical Perspective

    Alhussein Fawzi;Seyed-Mohsen Moosavi-Dezfooli;Pascal Frossard

  • Clustering With Multi-Layer Graphs: A Spectral Perspective

    Xiaowen Dong;Pascal Frossard;P. Vandergheynst;N. Nefedov

  • Joint source/FEC rate selection for quality-optimal MPEG-2 video delivery

    P. Frossard;O. Verscheure

  • Graph Signal Processing for Machine Learning: A Review and New Perspectives

    Xiaowen Dong;Dorina Thanou;Laura Toni;Michael Bronstein

  • SparseFool: A Few Pixels Make a Big Difference

    Apostolos Modas;Seyed-Mohsen Moosavi-Dezfooli;Pascal Frossard

  • Multiscale event detection in social media

    Xiaowen Dong;Dimitrios Mavroeidis;Francesco Calabrese;Pascal Frossard

  • Video Packet Selection and Scheduling for Multipath Streaming

    D. Jurca;P. Frossard

  • IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY Editor-in-Chief

    Chang Wen Chen;Hamid Gharavi;Thomas Sikora;Ishfaq Ahmad

Frequent Co-Authors

Pierre Vandergheynst
Pierre Vandergheynst École Polytechnique Fédérale de Lausanne
Jacob Chakareski
Jacob Chakareski New Jersey Institute of Technology
Gene Cheung
Gene Cheung York University
Antonio Ortega
Antonio Ortega University of Southern California
Fernando Pereira
Fernando Pereira Instituto Superior Técnico
Christophe De Vleeschouwer
Christophe De Vleeschouwer Université Catholique de Louvain
Daniel Kressner
Daniel Kressner École Polytechnique Fédérale de Lausanne
Andrea Cavallaro
Andrea Cavallaro Queen Mary University of London
Chang Wen Chen
Chang Wen Chen Hong Kong Polytechnic University
Thomas Sikora
Thomas Sikora Technical University of Berlin

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