My thesis title is Sparse Semi-Parametric Recovery of Astronomical Radio-Images. Its goal is to develop new signal processing tools to reconstruct image acquired from radio telescopes. The main topics that I work on are inverse problems, convex optimization and machine learning.
During the first year of my thesis, I worked on a new approach to measure cosmological parameters for Weak Gravitational Lensing. To do so, I mainly contributed in the development of a plug-and-play shape constraint and tested it on a sparse restoration algorithm. For the second year, I plan to delve into machine learning to continue developing reconstruction tools for radio astrophysics.
Conferences & Talks
- SPIE Wavelets and Sparsity XVIII, San Diego, USA, August 2019 (talk).
- Image Restoration Talk at SDSU Dep. of Math. and Stat., San Diego, USA, August 2019 (speaker).
- Wavelets and Beyond, Orsay, France, June 2019.
- 2018-2020 : Teaching assistant, Signals & Systems at Paris-Diderot university, Paris, France.
- 2019-2020 : Teaching assistant, Circuits & Architecture at Paris-Diderot university, Paris, France.
Courses & Workshops
- Sparsity4PSL, Paris, France, June 2019 (summer school).
- Deep Learning in Practice, Gif-sur-Yvette, France, Fall 2019 (MVA Master course).
- Science Writing EDP Sciences, Gif-sur-Yvette, France, February 2019 (workshop).
Previously to my PhD studies
- Engineering degree, specialized in Image Processing, IMT Atlantique, Brest, France, September 2018.
- SISEA Masters II in Research, specialized in Image Processing, IMT Atlantique, Brest, France, September 2018.
- BS in Mathematics, University of Western Brittany, Brest, France, June 2016.
- Preparatory classes, Math and Physics option, Saint Joseph University, Beirut, Lebanon, June 2015.
I am expected to defend my PhD in October, 2021, at CEA Paris-Saclay.
Last updated: September 2019