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FNRS Senior Research Associate and Professor

UCLouvain, Belgium

Biography

I am a Professor and FNRS Senior Research Associate at the Image and Signal Processing Group (ISPGroup), in the Mathematical engineering (INMA) department of the ICTEAM institute at UCLouvain, Belgium. My main research activities focus on compressive sensing (theory and applications), inverse problems solving in optics, astronomy and biomedical sciences, compressive learning and data sciences, sparse signal representations and other low-complexity signal priors.

Interests

  • Inverse Problems in Optics, Astronomy, and Biomedical Sciences

  • Compressive Sensing and Computational Imaging

  • Compressive Learning and Data Sciences

  • Image and Signal Processing

Education

  • PhD in Mathematical Physics, 2004

    UCLouvain, Belgium

  • MSc in Mathematical Physics, 1998

    UCLouvain, Belgium

  • BSc in Physics, 1996

    UCLouvain, Belgium

Appointments

  • IEEE Transactions on Signal Processing - Associate Editor (2022-now)

  • EURASIP Journal on Advances in Signal Processing - Associate Editor (2020-2022)

  • EURASIP Signal and Data Analytics for Machine Learning - Technical Area Committee member

Events

Recent & upcoming talks, seminars, …

Asymmetric compressive learning guarantees with applications to quantized sketches
Jun 20, 2022 — Jun 24, 2022 Minisymposium on Sparsity, optimization and learning, organized by Clarice Poon (U. Bath, UK), at 10th International Conference on Curves and Surfaces Arcachon, France
invited talk compressive statistical learning quantization GMM k-means
Slides
FNRS Contact Group - "Wavelets and applications", December 14th, 2021, UCLouvain, Belgium
Dec 14, 2021 Virtual UCLouvain
workshop organization
Event URL
Interferometric Lensless Endoscopy: Rank-one Projections of Image Frequencies with Speckle Illuminations
Oct 31, 2021 — Nov 3, 2021 Special session on "Computational Sampling", organized by Ayush Bhandari (Imperial College, UK), Asilomar, 2021 Virtual Asilomar, USA
invited talk rank-one projection interferometry lensless imaging endoscopy
Slides Video (mp4, 55Mb)
Interferometric Lensless Endoscopy: Rank-one Projections of Image Frequencies with Speckle Illuminations
Oct 7, 2021 Séminaire Images Optimisation et Probabilités Image Optimisation et Probabilités, CNRS, IMB Université Bordeaux
invited seminar rank one projection interferometry speckle lensless
The importance of phase in complex compressive sensing
Sep 10, 2021 "AI for signal and image processing" meeting Institut Pascal, Paris-Saclay University (France)
invited keynote complex phase compressive sensing
Video Slides demo (1) ipynb (1) demo (2) ipynb (2)
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Posts

Last 3 posts …

ROP inception

Here is a new short preprint: “ROP inception: signal estimation with quadratic random sketching”, available here and on arXiv. This is the first work of Rémi Delogne, carried out in collaboration with Vincent Schellekens and me.
May 19, 2022 4 min read
ROP inception

There is time for dithering in a quantized world of reduced dimensionality!

I’m glad to announce here a new work made in collaboration with Valerio Cambareri (UCL, Belgium) on quantized embeddings of low-complexity vectors, such as the set of sparse (or compressible) signals in a certain basis/dictionary, the set of low-rank matrices or vectors living in (a union of) subspaces.
Jul 6, 2016 12 min read
There is time for dithering in a quantized world of reduced dimensionality!

Quasi-isometric embeddings of vector sets with quantized sub-Gaussian projections

\(\newcommand{\cl}{\mathcal}\newcommand{\mathbb}{\mathbb}%\) Last January, I was honored to be invited in RWTH Aachen University by Holger Rauhut and Sjoerd Dirksen to give a talk on the general topic of quantized compressed sensing.
Apr 28, 2015 12 min read
Quasi-isometric embeddings of vector sets with quantized sub-Gaussian projections
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Most recent publications

(preprints, conference & journal papers)

Rémi Delogne, Vincent Schellekens, Laurent Jacques (2022). ROP inception: signal estimation with quadratic random sketching.

arXiv PDF

Vincent Schellekens, Laurent Jacques (2022). Asymmetric compressive learning guarantees with applications to quantized sketches. IEEE Transactions on Signal Processing.

Cite DOI arXiv

Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk (2021). The Separation Capacity of Random Neural Networks. DeepMath” (virtual event), November 4, 2021..

Rémi Gribonval, Antoine Chatalic, Nicolas Keriven, Vincent Schellekens, Laurent Jacques, Philip Schniter (2021). Sketching Datasets for Large-Scale Learning.

Cite DOI arXiv DIAL

Sjoerd Dirksen, Martin Genzel, Laurent Jacques, Alexander Stollenwerk (2021). The Separation Capacity of Random Neural Networks.

arXiv

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