World's Best Scientists 2026 revealed!

Overview

Laurent Daudet is affiliated with Université Paris Cité in France. Their research primarily spans the fields of engineering and computer science, with a particular focus on electrical and electronic engineering, artificial intelligence, computational mechanics, signal processing, and molecular biology.

The scientist has contributed extensively to a range of interdisciplinary topics, including:

  • Neural Networks and Reservoir Computing
  • Optical Network Technologies
  • Photonic and Optical Devices
  • Advanced Adaptive Filtering Techniques
  • Speech and Audio Processing
  • Acoustic Wave Phenomena Research
  • Gene Regulatory Network Analysis

Laurent Daudet's publication record includes papers published in notable venues such as arXiv (Cornell University), IEEE/ACM Transactions on Audio Speech and Language Processing, Optics Express, Photoniques, and HAL (Le Centre pour la Communication Scientifique Directe). These venues reflect the interdisciplinary nature of their work, spanning both theoretical and applied domains.

Recent papers highlight key areas of exploration and are presented as follows:

  • Optimizing Source and Sensor Placement for Sound Field Control: An Overview, 2020, IEEE/ACM Transactions on Audio Speech and Language Processing
  • Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment, 2020, arXiv (Cornell University)
  • High-fidelity and large-scale reconfigurable photonic processor for NISQ applications, 2022, Optics Express
  • Light-in-the-loop: using a photonics co-processor for scalable training of neural networks, 2020, arXiv (Cornell University)
  • Streamlined optical training of large-scale modern deep learning architectures with direct feedback alignment, 2024, arXiv (Cornell University)

The collaboration network of Laurent Daudet includes frequent coauthors such as Igor Carron, Sylvain Gigan, Iacopo Poli, Florent Krząkała, and Julien Launay. These collaborations suggest active engagement with experts in both photonics and neural network fields.

Laurent Daudet's work addresses complex challenges related to sound field control, photonic processors for quantum and neural network applications, and advanced training architectures utilizing optical computation. This research intersects hardware development, adaptive signal processing, and machine learning paradigms.

Best Publications

  • Machine learning and the physical sciences

    Giuseppe Carleo;J. Ignacio Cirac;Kyle Cranmer;Laurent Daudet

  • A tutorial on onset detection in music signals

    J.P. Bello;L. Daudet;S. Abdallah;C. Duxbury

  • Sparse Representations in Audio and Music: From Coding to Source Separation

    Mark D Plumbley;Thomas Blumensath;Laurent Daudet;Remi Gribonval

  • Imaging with nature: compressive imaging using a multiply scattering medium.

    Antoine Liutkus;David Martina;Sébastien Popoff;Gilles Chardon

  • 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

  • Near-field acoustic holography using sparse regularization and compressive sampling principles.

    Gilles Chardon;Laurent Daudet;Antoine Peillot;François Ollivier

  • Parametric Dictionary Design for Sparse Coding

    M. Yaghoobi;L. Daudet;M.E. Davies

  • Kernel Additive Models for Source Separation

    Antoine Liutkus;Derry Fitzgerald;Zafar Rafii;Bryan A Pardo

  • Sparse and structured decompositions of signals with the molecular matching pursuit

    L. Daudet

  • Hybrid representations for audiophonic signal encoding

    L. Daudet;B. Torrésani

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

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

  • Methodology and Tools for the evaluation of automatic onset detection algorithms in music.

    Laurent Daudet;Gaël Richard;Pierre Leveau

  • Instrument-Specific Harmonic Atoms for Mid-Level Music Representation

    P. Leveau;E. Vincent;G. Richard;L. Daudet

  • Convex Optimization Approaches for Blind Sensor Calibration Using Sparsity

    Cagdas Bilen;Gilles Puy;Rémi Gribonval;Laurent Daudet

  • Sparse Linear Regression With Structured Priors and Application to Denoising of Musical Audio

    C. Fevotte;B. Torresani;L. Daudet;S.J. Godsill

  • Automatic Piano Transcription Using Frequency and Time-Domain Information

    J.P. Bello;L. Daudet;M.B. Sandler

  • MDCT analysis of sinusoids: exact results and applications to coding artifacts reduction

    L. Daudet;M. Sandler

  • Boltzmann Machine and Mean-Field Approximation for Structured Sparse Decompositions

    A. Dremeau;C. Herzet;L. Daudet

  • Union of MDCT Bases for Audio Coding

    E. Ravelli;G. Richard;L. Daudet

  • SparseRepresentationsinAudio and Music: From Coding to Source Separation The fidelity of music and other audio can usually be accurately and rapidly predicted from a relatively small sample of signal information.

    Mark D. Plumbley;Thomas Blumensath;Laurent Daudet;Remi Gribonval

Frequent Co-Authors

Gael Richard
Gael Richard Télécom ParisTech
Rémi Gribonval
Rémi Gribonval École Normale Supérieure de Lyon
Florent Krzakala
Florent Krzakala École Polytechnique Fédérale de Lausanne
Mark Sandler
Mark Sandler Google (United States)
Laurent Girin
Laurent Girin Grenoble Institute of Technology
Bertrand David
Bertrand David Télécom ParisTech
Roland Badeau
Roland Badeau Télécom ParisTech
Juan Pablo Bello
Juan Pablo Bello New York University
Albert Cohen
Albert Cohen Google (United States)
Martin Vetterli
Martin Vetterli École Polytechnique Fédérale de Lausanne

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring a Computer Science degree in the USA can open the door to many rewarding tech careers. For those considering advanced studies, finding the best masters degree to get can give you a competitive edge in the job market. Specializing in in-demand areas such as data science, cybersecurity, or artificial intelligence is especially valuable.

If you prefer a shorter and more flexible option, online associate degree programs offer foundational skills for entry-level jobs, and credits can often be transferred to a bachelor’s degree later on.

Budget is an important consideration for many students. Today, there are many affordable online degree programs that provide high-quality education at a reasonable cost, helping you minimize student debt.

Don’t be discouraged if your academic history isn’t perfect. There are also online graduate schools with low gpa requirements that welcome applicants from diverse backgrounds—making higher education more accessible than ever before.

Best Scientists Citing Laurent Daudet

Trending Scientists

Recently Published Articles