cv

A short academic resume. More details can be found in the pdf at the right on the page.

General Information

Full Name Florian Sarron
Languages French, English

Education

  • 2018
    PhD
    Sorbonne Université / IAP, Paris, France
    • Galaxy clusters in the cosmic web
    • Under supervision of Florence Durret (IAP) and Christophe Adami (LAM)
  • 2015
    Master 2
    Université Paris Diderot - Paris 7 - Observatoire de Paris Meudon (OBSPM)

Experience

  • 2024 - now
    Postdoctoral researcher
    Institut de Recherche en Informatique de Toulouse (IRIT) / Centre de Biologie Intégrative (CBI), Toulouse, France
    • Postdoctoral researcher in the Mambo team (PI - Pierre Weiss)
    • Optimizing optical micoscope using Deep Learning and Bayesian Statistics
    • Projects
      • ANR MicroBlind - Optical fluorescence microscope blind deblurring using deep unrolled networks
      • Instance segmentation of cells in images of biological samples with partial annotations using physics and deep learning.
  • 2022 - 2024
    CNES Postdoctoral Fellow
    Institut de Recherche en Astrophysique et Planétologie (IRAP), Toulouse, France
    • PI of the CNES fellowship PICTOGALE "Photometric investigation of cluster of galaxies toward Euclid"
    • Active member of the Euclid consortium, GOGREEN collaboration and XCLASS collaboration
  • 2019 - 2022
    Postdoctoral researcher
    University of Manchester / University of Nottingham, UK
    • Postdoctoral researcher in the team of Chris Conselice
    • Studying galaxy evolution in cluster and groups up to redshift z = 2.5 in deep near-infrared surveys (COSMOS, UDS, ...)

Open Source Projects

  • 2024-now
    DeepInv (contributor)
    • Deep Inverse is an open-source pytorch library for solving imaging inverse problems using deep learning.
  • 2020-now
    DETECTIFz (lead)
    • DETECTIFz is a galaxy group finder for multibnad photometric surveys, leveraging multi-dimensionnal posteriors from SED fitting codes.

Academic Interests

  • Data analysis
    • Image analysis using deep learning (Blind deblurring, image segmentation)
    • (Hierarchichal) Bayesian modelling of data with uncertain observations
    • Data clustering with uncertain observations (in astrophysics - galaxy cluster detection)
  • Extragalactic Astrophysics
    • Deciphering the role of environment on galaxy star-formation evolution
    • Improving information extraction from photometric surveys with statistical modeling

Other Interests

  • Low-carbon science and sustainability of research (member of study group in IRAP)