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

D-Index & Metrics

Computer Science

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

Electronics and Electrical Engineering

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

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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