Projects

My objective is to deal with entire missing rows in supervised block-structured data sets. As a spicy detail data sets are build on a few participants and a lot of variables.

Publications

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

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

In the supervised high dimensional settings with a large number of variables and a low number of individuals, one objective is to …

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

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

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

Talks and posters

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

Les récentes innovations techniques ont permis la production de données massives en biologie, comme les données omiques par exemple …

This is the last update of the current project on dealing with missing samples in multi-block context for supervised datasets.

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

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

Using the Meso Scale Discovery (MSD) V-PLEX 40 biomarker cytokine multiplex kit, the cytokine profiles of 108 HIV+ Zambian volunteers …

Teaching

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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 2016 – Present
Bordeaux

PhD student

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

70%

Overleaf

70%

Python

60%

Contact

  • +335 57 57 13 93
  • Université de Bordeaux, 146 Rue Léo Saignat, 33000 Bordeaux, France