PhD Student
BioSP, Inrae, Avignon
ED 536, Sciences Agronomiques, Université d’Avignon
camille.portes~at~inrae.fr
About
I am a PhD student interested in the use of Machine Learning in Agriculture, Environment and Ecology. My advisors are Edith Gabriel, Dino Ienco and Eric Verdin.
I work on machine learning models to predict the presence of the bacterium Xylella fastidiosa. The objective is to identify the factors correlated with the presence of the bacterium and to provide risk maps. The model proposed is designed to take into account the data specificities as spatial autocorrelation and geographic heterogeneity.
My PhD is funded by Implanteus and is also part of the BEYOND project.
Publications
- "Environmental and bioclimatic data for epidemiological analysis over French Mediterranean areas",
Environmental Data Science, 2025
Talks
- 05/12/2024: Groupe de Travail Surveillance Xylella fastidiosa, Paris
- 28/05/2024: Journées de Statistique de la SFdS, Bordeaux
- 05/07/2022: Summer School TISS1, Avignon
- 02/06/2022: Towards Pesticide Free Agriculture - What research to meet the pesticides reduction objectives embedded in the European Green Deal?, Dijon
Teaching
- 2024/2025 : Descriptive Statistics - Bivariate Part (21h)
- 2023/2024 : Descriptive Statistics - Univariate Part (21h), Basic Statistical Programming in R (39h)
- 2022/2023 : Descriptive Statistics - Univariate Part (9h), Basic Statistical Programming in R (39h)
Students
- 2024 : Co-supervisor of a Bachelor student for a 3 months internship
Short Vitae
- 2021 - ... : PhD Student,
ED 536 Sciences Agronomiques, Avignon and BioSP, Inrae - 2019 - 2021: Master Statistics and Econometrics
Toulouse School of Economics - 2015 - 2018: Bachelor Economics and Mathematics
Toulouse School of Economics