Matthieu Simeoni

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matthieu.simeoni@epfl.ch +41 21 693 56 36 https://matthieumeo.github.io/

Citizenship : Française

Birth date : 26.08.1991

About
I am a postdoctoral researcher and lecturer at EPFL at the Audiovisual Communications Laboratory. My research focuses on developing data science methods for large scale geo-environmental monitoring. I believe indeed that the current environmental challenges call for informed data-driven policies. More precisely, I specialise in the reconstruction of partially observed natural phenomena globally distributed at the Earth's surface. My approach is based on a novel continuous-domain spherical approximation framework developed during my PhD thesis, co-supervised by Pr. Martin Vetterli, Pr. Victor Panaretos and Pr. Paul Hurley. I am also in charge of recruiting and supervising PhD and Master students, as well as writing and managing multiple research grants. Finally, I am also a lecturer for the Master-level class Mathematical Foundations of Signal Processing.


EPFL IC IINFCOM LCAV
BC 322 (Bâtiment BC)
Station 14
CH-1015 Lausanne

Web site: Web site: https://lcav.epfl.ch/

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Administrative data


Professional course

Research Data Scientist

I was a member of the Foundations of Cognitive Solutions research group at IBM Zurich, under the supervision of Pr. Paul Hurley.

IBM Research Zurich

2014-2020


Education

Docteur ès Sciences (PhD)

"Functional Inverse Problems on Spheres: Theory, Algorithms and Applications" Advisors: Prof. Martin Vetterli, Prof. Victor Panaretos and Prof. Paul Hurley.

EPFL

2015-2019

Master of Science

Applied Mathematics

EPFL

2013-2015

Bachelor of Science

Mathematics

EPFL

2011-2013

Classes Préparatoires aux Grandes Écoles

Mathematics and Physics

CIV, Sophia Antipolis, France

2009-2011

Baccalauréat Scientifique

Specializing in Mathematics and Physics

Lycée Thierry-Maulnier

2009


Awards

IBM Research Prize in Computational Science

This prize promotes research in computational sciences and recognizes outstanding master theses focused on advanced modelling and simulation methods.

2015

Publications

Infoscience publications

Teaching & PhD

Teaching

Communication Systems

Courses

Mathematical foundations of signal processing

Signal processing tools are presented from an intuitive geometric point of view which is at the heart of all modern signal processing techniques. The student will develop the mathematical depth and rigor needed for the study of advanced topics in signal processing and approximation theory.