Hadrien Lorenzo

Associate Professor

Aix Marseille Université

Biography

I am an 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!

Interests

Statistical modelling
Missing Value Treatment
Variable selection
SIR
Bootstrap
Extreme Value Theory
Bayesian Statistics
PLS
Machine Learning
Teaching

Education

PhD in Biostatistics, 2019

Université de Bordeaux
Research Master, Applied Mathematics for Image and Signal Processing, 2015

CentraleSupelec and Paris-Sud University

Publications

Computational Outlier Detection Methods in Sliced Inverse Regression

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

H Lorenzo, J Saracco

PDF DOI

The relationships between Sensory and Nutritional Quality are not consistent from one muscle to another in the same bovine carcass

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

MP Ellies-Oury, D Gruffat, A Listrat, H Lorenzo, M Chavent, J Saracco

PDF

Advanced topics in Sliced Inverse Regression

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

S Girard, H Lorenzo, J Saracco

PDF Source Document

Data-Driven Sparse Partial Least Squares

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

H Lorenzo, O Cloarec, R Thiebaut, J Saracco

PDF Source Document DOI

ddsPLS: A Package to Deal with Multiblock Supervised Problems with Missing Samples in High Dimension

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

H Lorenzo, J Saracco, R Thiebaut

PDF

An Original Methodology for the Selection of Biomarkers of Tenderness in Five Different Muscles

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

MP Ellies-Oury, H Lorenzo, C Denoyelle, C Denoyelle, J Saracco, B Picard

PDF Source Document

High-dimensional multi-block analysis of factors associated with thrombin generation potential

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

H Lorenzo, M Razzaq, J Odeberg, PE Moreange, J Saracco, DA Tregouet, R Thiebaut

PDF Source Document

Une PLS multivoie parcimonieuse avec observations manquantes pour données hétérogènes

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

H Lorenzo, R Thiebaut, J Saracco

PDF

Systems Vaccinology Identifies an Early Innate Immune Signature as a Correlate of Antibody Responses to the Ebola Vaccine rVSV-ZEBOV

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

A Rechtien, L Richert, H Lorenzo, G Martrus, B Hejblum, C Dahlke, R Kasonta, M Zinser, H Stubbe, U Matschl, A Lohse, V Krähling, M Eickmann, S Becker, VEBCON Consortium, R Thiebaut, M Altfeld, M Addo

PDF Source Document DOI

Talks and posters

More Talks

Sélection de variables en régression SIR par seuillage doux/dur de la matrice d'intérêt.

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

H Lorenzo, J Saracco, C Weinreich

PDF

Imputation for supervised learning problems in high dimension

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

H Lorenzo, O Cloarec, J Saracco

PDF

Koh-Lanta, missing data imputation in supervised context

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

H Lorenzo, O Cloarec, J Saracco

PDF

Detection of atypical individuals in SIR regression

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

H Lorenzo, J Saracco

PDF Video

How to deal with missing values in the high dimensional supervised context?

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

H Lorenzo, O Cloarec, J Saracco

PDF

Multiblock supervised analyses. Should we really normalize blocks?

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

H Lorenzo, R Thiebaut, J Saracco, O Cloarec

PDF

Détection d’individus atypiques en régression SIR.

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)

H Lorenzo, J Saracco

PDF

High-dimensional multi-block analysis of factors associated with thrombin generation potential

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

H Lorenzo, M Razzaq, J Odeberg, PE Morange, J Saracco, DA Trégouët, R Thiébaut

PDF

Apprentissage supervisé pour données massives multi-blocs incomplètes

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

H Lorenzo, R Thiebaut, J Saracco

PDF

A mono/multi-block sparse PLS for heterogeneous data with missing samples

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

H Lorenzo, R Thiebaut, J Saracco

PDF

Teaching

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%

about

Hadrien Lorenzo

Associate Professor

Biography

Interests

Education

Publications

Talks and posters

Teaching

Experience

PostDoc

PhD

Research Engineer

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

CentraleSupelec and Montreal Polytechnique University

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

CentraleSupelec and GE Healthcare

Astrophysics - Image Processing for large structure studies, internship

Skills

R

Statistics

Overleaf

Python

Contact