Curriculum Vitae

Education

• Ph.D in Statistical signal processing applied to radio-interferometry, SATIE/Université Paris-Saclay, Gif-sur-yvette, France - 2023
• M.S. in Electronics and signal processing, ENSEEIHT, Toulouse, France - 2015-2018

Professional Experience

Associate professor

2024-present - LISTIC/Université Savoie Mont Blanc - Annecy, France

Postdoctoral Researcher

2023-2024 - MAP5/Université Paris-Cité - Paris, France

• Currently working in the Image group with Andrés Almansa, Rémy Abergel, and Lionel Moisan on hyperspectral image reconstruction. Collaborating with Mauro Dalla-Mura from Gipsa-Lab for the ANR project Fu-MultiSpoc, aiming at building a high-resolution hyperspectral imager based on a Fabry Perot interferometer.
• Research focus includes hyperspectral image denoising, image restoration, and plug-and-play approaches to inverse problems.

Doctoral Researcher

2020-2023 - Université Paris-Saclay/SATIE - Gif-Sur-Yvette, France

• Developed novel statistical signal processing methodologies for calibration and imaging in radio-interferometric data, considering the presence of interferences.
• Research Themes: Statistical learning, deep neural networks, inverse problems, radio-interferometry.
• Contributions:
  • Published in national and international journals and conferences.
  • Contributed to the python library (pfb-clean) dedicated to radio-interferometric imaging on voluminous data for the MeerKat radio telescope.
  • Taught C++ module, image processing, and telecommunications systems in the fourth year of engineering school.
  • Proficient in Python, C++.
  • Received training in science communication and outreach.

R&D Algorithm Engineer

2019-2020 - Phasics - St-Aubin, France

• Led the design and development of signal and image processing tools for the analysis of interferometric data from wavefront analyzers, with applications in laser beam characterization, phase microscopy, and optical characterization.
• Projects:
  • Developed a Python library dedicated to wavefront data analysis.
  • Created a C library dedicated to Zernike polynomial calculations.
  • Applied machine learning for temperature calibration of wavefront analyzers.
  • Developed image processing solutions for the detection of Gaussian sources in interferograms.

Research Intern

2018 - IRIT/CNRS - Toulouse, France

• Conducted research on deep learning-informed phase estimation for audio source separation under the supervision of Cédric Fèvotte and Thomas Oberlin.
• Utilized non-negative matrix factorization (NMF) for audio source separation.
• Implemented deep neural networks for phase estimation in the context of audio source separation using TensorFlow.

Research Intern

2017 - AAU Aalborg Copenhagen - Copenhagen, Denmark

• Worked on the development of a Generative Adversarial Network (GAN) for generating percussive sounds under the guidance of Hendrick Purwins.
• Utilized TensorFlow for the implementation of the GAN.

Reviewing Activities

• IET Signal Processing
• IEEE Transactions on Image Processing
• Elsevier Signal Processing
• EUSIPCO Conference

Teaching experience

• 2020 - 2023: Associate teacher in an image processing course at Polytech Paris-Saclay.
• 2022 - 2023: Associate teacher in a telecommunication course at Polytech Paris-Saclay.
• 2020 - 2022: Associate teacher for an Advanced C++ course at Polytech Paris-Saclay.

Skills

Programming Langages: Python, C/C++, bash, html/css
Documents : Latex, Office Suite