Star

Publications

This research focuses on dimension-reduction techniques for modeling conditional extreme values. Specifically, we investigate the idea …
PDF Source Document

Sliced inverse regression (SIR) focuses on the relationship between a dependent variable $y$ and a $p$-dimensional explanatory variable …
PDF DOI

The sensory and nutritional qualities of meats are strong expectations for consumers. However, these two types of quality are sometimes …
PDF

Since its introduction in the early 90’s, the Sliced Inverse Regression (SIR) methodology has evolved adapting to increasingly complex …
PDF Source Document

In the supervised high dimensional settings with a large number of variables and a low number of individuals, variable selection allows …
PDF Source Document DOI

The ddsPLS method considers regression and classification problems in the context of multiblock structured covariate data sets taking …
PDF

For several years, studies conducted for discovering tenderness biomarkers have proposeda list of 20 candidates. The aim of the present …
PDF Source Document

The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains …
PDF Source Document

Several sets of variables can be analyzed simultaneously by canonical correlation in a multi-way analysis. These sets of variables are …
PDF

Predicting vaccine efficacy remains a challenge. We used a systems vaccinology approach to identify early innate immune correlates of …
PDF Source Document DOI

Talks and posters

More Talks

An interesting feature of Sliced Inverse Rregression (SIR) is that it allows the construction of indices, as linear combinations of the …
Jun 16, 2022 12:00 AM 53èmes Journées de Statistique - JDS 2022
PDF

The problem of missing data often occurs in data analysis. Missing values of the type MAR (Missing At Random) are cosidered here. Then, …
Jun 8, 2022 12:00 AM Compstat 2022, Bologne
PDF

The imputation is the process that estimates the missing values. Simplest approaches impute to fixed values such as mean/median based …
Jun 8, 2022 12:00 AM 23ème Congrès de Chimiométrie, Université de Bretagne Occidentale, Brest, Juin 2022
PDF

How can we deal with atypical observations in SIR regression. This can be generalized to any predictive model.
Feb 10, 2022 2:00 PM Dataquitaine 2022, Talence, France
PDF Video

A reflexion about missing data imputation in the supervised context, with a solution and simulation results.
Dec 19, 2021 12:00 AM CMStatistics 2021, King’s College London, UK
PDF

In recent years, data analysis methods have had to deal with new type of heterogeneous data sets. Multi-omics studies are perfect …
Sep 8, 2021 12:00 AM 17th Scandinavian Symposium on Chemometrics
PDF

Sliced inverse regression (SIR) focuses on the relationship between a dependent variable $y$ and a $p$-dimensional explanatory variable …
Jun 9, 2021 12:00 AM 52èmes Journées de Statistique de la Société Française de Statistique (SFdS)
PDF

The identification of novel biological factors associated with thrombin generation, a key biomarker of the coagulation process, remains …
Jun 6, 2019 12:00 AM 32nd IEEE CBMS International Symposium on Computer-Based Medical Systems – CBMS2019
PDF

Les récentes innovations techniques ont permis la production de données massives en biologie, comme les données omiques par exemple …
May 16, 2019 12:00 AM Journée de l’Ecole doctorale EDSP2 2019 - JEDSP2 2019
PDF

This is the last update of the current project on dealing with missing samples in multi-block context for supervised datasets.
Jul 5, 2018 12:00 AM Séminaire de Biostatistiques
PDF

Teaching

*
All English French R Python Health and Science Statistical Learning

How to deal with missing values, 2022

Some new things.

How to deal with missing values, 2021

What are missing values and how to deal with them using R classical packages.

Partial Least Squares (PLS), an introduction

What is PLS and why ?

Introduction à l'apprentissage statistique

That course shows main goals of statistical learning detailing bias/variance tradeoff and most of my thesis results.

Genetics project in the context of high dimensional data

That course shows main goals of supervised and unsupervised methods to help students to prepare a project dealing with the 10X data set.

Supervised and unsupervised analysis for high dimensinal data

That course shows main goals of supervised and unsupervised methods and their applications through the spectrum of my proper applications.

PLS and sparse PLS

Introduction to PLS (Partial Least Square) and one of its sparse versions.

Maths and function analysis

Mathematical courses designed to fit to French second year medical students of the Double Cursus Sante Sciences expecting strong mathematical bases.

Maths and linear algebra

Mathematical courses designed to fit to French second year medical students of the Double Cursus Sante Sciences expecting strong mathematical bases.

Statistics and Probability

Mathematical courses designed to fit to second year medical students expecting strong mathematical bases.

Single-cell datasets visualizations : PCA Versus tSNE

Among new RNA sequencing methods, one permits to detail the RNA (or DNA) of a sample at a cellular level. That is the Single-Cell RNA-seq. That course explores methods to visualize those datasets.

Experience

 
 
 
 
 
October 2019 – Present
Talence

PostDoc

ASTRAL team

Perform high dimensional analyses through statistical modeling keeping interpretability
 
 
 
 
 
October 2016 – October 2019
Bordeaux

PhD

SISTM team, U1219

Data analysis and eigen-space decomposition for supervised problems. Compressing many thoughts :

Missing Value + High-dimension = Act carefully

 
 
 
 
 
October 2015 – October 2016
Bordeaux

Research Engineer

SISTM team, U1219

Discover public health and its tools.
 
 
 
 
 
February 2015 – August 2015
Châtenay-Malabry/Montréal

Bayesian approach selecting optimal classes of structural models in earthquake analysis for beam structures, internship

CentraleSupelec and Montreal Polytechnique University

Finite elements modelisation and real application to bridge movements with Fourier analysis. Great teams and amazing moments!
 
 
 
 
 
September 2014 – January 2015
Gif-sur-Yvette

Identification of prognostic factors in hepato-cellular carcinoma surgery, project

CentraleSupelec and GE Healthcare

A team project dedicated to image segmentation using SVM tools and morphological transformation. A work done in cooperation with GE Healthcare and supervised by Arthur Tenenhaus and Laurent Le Brusquet.
 
 
 
 
 
June 2014 – September 2015
Nice

Astrophysics - Image Processing for large structure studies, internship

Lagrange Laboratory

Extra large images implying special dedicated tools such as spherical wavelets but also deeply open minds. What else to say ? It is hard!

Skills

R

80%

Statistics

100%

Overleaf

70%

Python

60%

Contact

  • 3 Place Victor Hugo, Aix-Marseille University, I2M, Marseille, France
about

+++

About/Biography widget.

widget = “about” active = true date = 2016-04-20T00:00:00

Order that this section will appear in.

weight = 1

List your academic interests.

[interests] interests = [ “Statistical modelling”, “Missing Value Treatment”, “Variable selection”, “SIR”, “Bootstrap”, “Extreme Value Theory”, “Bayesian Statistics”, “PLS”, “Machine Learning”, “Teaching” ]

List your qualifications (such as academic degrees).

\[\[education.courses\]] course = “PhD in Biostatistics” institution = “Université de Bordeaux” year = 2019

\[\[education.courses\]] course = “Research Master, Applied Mathematics for Image and Signal Processing” institution = “CentraleSupelec and Paris-Sud University” year = 2015

+++

Biography

I am a Associate Professor at Aix-Marseille University (AMU). I teach for all university degrees at the AMU. My reserches are performed in the Statistical group of the ALEA team, one of the teams of the Institut de Mathématiques de Marseille (I2M, UMR 7373).

I currently teach to

I2M is an Joint Research Unit (UMR in french) placed under the triple tutelage of the CNRS, AMU and the École Centrale de Marseille.

I unreasonably work on R and you can view the current stage on my packages on GitHub. My wish is to be useful to both of the communities which have so much to share!

+++

About/Biography widget.

widget = “about” active = true date = 2016-04-20T00:00:00

Order that this section will appear in.

weight = 1

List your academic interests.

[interests] interests = [ “Statistical modelling”, “Missing Value Treatment”, “Variable selection”, “SIR”, “Bootstrap”, “Extreme Value Theory”, “Bayesian Statistics”, “PLS”, “Machine Learning”, “Teaching” ]

List your qualifications (such as academic degrees).

[education.courses] course = “PhD in Biostatistics” institution =“Université de Bordeaux” year = 2019

[education.courses] course = “Research Master, Applied Mathematics for Image and Signal Processing” institution = “CentraleSupelec and Paris-Sud University” year = 2015

+++

Biography

I am a Associate Professor at Aix-Marseille University (AMU). I teach for all university degrees at the AMU. My reserches are performed in the Statistical group of the ALEA team, one of the teams of the Institut de Mathématiques de Marseille (I2M, UMR 7373).

I currently teach to

I2M is an Joint Research Unit (UMR in french) placed under the triple tutelage of the CNRS, AMU and the École Centrale de Marseille.

I unreasonably work on R and you can view the current stage on my packages on GitHub. My wish is to be useful to both of the communities which have so much to share!