Audrey Poterie Doctor in Statistics - Weebly
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MSPGH, University of Melbourne
207-221 Bouverie Street, Parkville
Audrey Poterie VIC 3053, Melbourne, AUSTRALIA
T +61 4 52 52 75 74
B audrey.poterie@unimelb.edu.au
Í https://audreypoterie.weebly.com
Doctor in Statistics 28 years
I am a doctor in applied mathematics, specialty statistics. I defended my PhD thesis ion the 18th
of October 2018 at IRMAR-INSA in Rennes (France). From November 2018, I have been working
as a research fellow in statistics in the University of Melbourne in the Centre for Epidemiology and
Biostatistic Research.
My research fields are biostatistics. During my PhD, I have studied more particularly the learning
methods and the algorithms of machine learning. Currently in postdoc in Melbourne, I am continuing
to study learning methods and especially machine learning algorithms. I am working on a new project
which deals about the development of machine learning approaches and particularly deep learning
methods and random forest algorithms to analyse MRI data.
My internships and my year as a biostatistician in the cancer research center Gustave-Roussy have
allowed us to study other research topics such as the application of causal methods for data collected in
oncology phase 1 trials, the analysis of longitudinal data and the survival analysis. I have also had the
opportunity to teach several topics in mathematics.
Interested both in the theoretical analysis of the statistical methods and the development of new methods
to address some real problems in medicine, biology and environment, after my PhD, I plan to continue
my research in statistics and to develop interdisciplinary collaborations. I am also interested in teaching
mathematics.
Education
2018 – 2015 Post-doctoral position in statistics, Centre for Epidemiology and Biostatistic
Research at the University of Melbourne, Melbourne (Australia), under the supervision
of Professor Julie Simpson.
2015 – 2018 PhD in Applied Mathematics, Statistics, IRMAR-INSA, University of Rennes 1,
Rennes (France), under the supervision of Jean-François Dupuy, Valérie Monbet and
Laurent Rouvière.
{ Title: Decision trees and random forests for grouped variables.
{ Main topic: Development and study of two new tree algorithms adapted to grouped data
and extension of the random forests algorithm to grouped variables.
{ Second topic: Statistical study of a robust hierarchical clustering algorithm in presence of
outliers.
{ keywords: Learning methods, tree-based approaches, random forests, grouped data, group
variable selection, biostatistics, clustering.
{ Implementation: Development of the R package named DTRFGV (the R package) and
the R functions TPLDA (the R functions).
{ Defended on the 18th of October 2018.
2013 – 2014 Second-Level Masters degree (M2 Research) in Mathematics Statistics, Uni-
versity of Rennes 1 (France).
{ Results: with high honors.2011 – 2014 Second-Level Masters degree in Statistics, Ecole Nationale Supérieure de la
Statistique et de l’Analyse de l’Information (ENSAI), Grande Ecole of the Grouping of
National Economics and Statistics Schools (GENES) Statistics and Operation Research,
Rennes (France).
{ Results: with high honors.
2010 – 2011 Bachelor degree in Mathematics, University of Angers, Angers (France).
{ Results: with highest honors.
Research Interests
From my PhD thesis, my research fields are:
{ Learning methods, supervised classification, decision trees, random forests, deep learning, algorithms
of machine learning.
{ Biostatistics.
{ Unsupervised clustering methods and their theoretical properties.
During my internships and my experience as a biostatistician, I also interested in the following research
fields:
{ Analysis of observational data, causal methods, survival analysis, parametric and semi-parametric
models, censored data, missing data, small samples, clinical trials, statistics in oncology.
{ analysis of longitudinal data, mixed models, additive models, multivariate adaptive regression splines
(MARS).
Experience
2014 – 2015 Biostatistician, Biostatistic and Epidemiology unit, Villejuif (France), under the
supervision of Dr Ellen Benhamou and Pr Stefan Michiels.
{ Research on propensity score based methods on small sample-size samples
{ Statistical analysis of clinical trials and observational studiess
{ Coauthoring of several publications about clinical trials and observational studies
{ Teaching activities for medical and engineering students.
20142015– Internship, Biostatistic and Epidemiology unit, Villejuif (France), under the supervi-
sion of Emilie Lanoy.
{ Topic: Performances of methods based on propensity score in Phase I database - Evaluation
of molecular oriented metastatic breast cancer drugs.
{ Duration: 6 months.
{ Research on application of propensity score based methods on small sample-size samples.
{ Communication at conferences.
20132015– Internship, Centre for clinical research and effective practice, Middlemore Hospital
and Auckland University of Technology, Auckland (New-Zealand), under the supervision
of Pr Alain Vandal.
{ Topic: Elaboration of a joint-model of foetal-tissues growth, analysis of the ethnicity
influence.
{ Duration: 2 months.
{ Research on mixed regression and growth curves modelling.
{ Development of new growth curves for the foetal-tissues according to the mother ethnicity.Teaching Experience
2019– 2019 Teaching assistant, University of Melbourne (Australia).
{ Linear regression (12h practical session, student in M1 of biostatistics) : simple
and multiple linear regression, statistical hypothesis testing, parameter estimation, confi-
dence intervals and prediction intervals, variable transformations and interactions, quality
adjustement, introduction to ANOVA.
2016 – 2018 Teaching assistant, INSA Rennes (France).
{ Probability tools for engineering (20h tutorial, third-year students): moment gen-
erating function, characteristic function, Gaussian vectors, central limit theorem, confidence
interval, test theory.
{ Introduction to probability and Statistics (44h tutorial, second-year student):
random variables, discrete distributions, density distributions, conditional probabilities,
independent events, joint probability distribution, marginal distribution.
2014 – 2015 Teaching assistant, ENSAI Rennes (France).
{ Analysis of variance (18h practical session, second-year student): one-way ANOVA,
two-way ANOVA, factorial design, identifiability constraints, hypothesis testing, parameter
estimation.
{ R language (47h practical session, first-year student) : introduction and basics,
variables and data types, inbuilt functions, data frames, plotting, writing functions, data
basic statistical data analysis procedures, plotting.
2015– 2018 Teaching assistant, Faculty of Medicine, Université Paris Sud (France).
{ Probability ans Statistic (6h, lecture course, oncology residents) : descriptive
statistics, basic probability distribution, hypothesis testing, confidence intervals.
Supervision
2019– 2019 Supervision of two students in M2 of biostatistics, research project in biostatis-
tics, University of Melbourne (Australia).
Publications
PhD thesis
[1] A. Poterie, Arbres de décision et forêts aléatoires pour variables groupées.
(ThesisAudreyPOTERIE.pdf).
Articles in statistical journals
[2] N. Klutchnikoff, A. Poterie and L. Rouvière, Statistical Analysis of a robust hierar-
chical clustering algorithm.. Ongoing submission. (Corresponds to the fourth chapter
in the PhD thesis).
[3] A. Poterie, J.-F. Dupuy, V. Monbet and L. Rouvière, CART trees and random forests
for grouped variables. Ongoing submission. (Corresponds to the third chapter in the
PhD thesis).
[4] A. Poterie, J.-F. Dupuy, V. Monbet and L. Rouvière, Classification tree algorithms
for grouped data and its application in microarrays. Accepted in Computational
Statistics.(preprint.pdf).
Articles in medical journals
[5] R. Bahleda, M.-C. Le Deley, A. Bernard, S. Chaturvedi, M. Hanley, A. Poterie, et al.
Phase I trial of bortezomib daily dose: safety, pharmacokinetic profile, biological effects
and early clinical evaluation in patients with advanced solid tumors. Investigational
New Drugs, 1-10, 2017.
[6] M. Gizzi, L. Oberic, C. Massard, A. Poterie, et al. Predicting and preventing
thromboembolic events in patients receiving cisplatin-based chemotherapy for germ
cell tumours. European Journal of Cancer, 59, 151-157, 2016.[7] C. Rodriguez, V. Suciu, A. Poterie, et al. Concordance between HER-2 status
determined by qPCR in Fine Needle Aspiration Cytology (FNAC) samples compared
with IHC and FISH in Core Needle Biopsy (CNB) or surgical specimens in breast
cancer patients. Molecular Oncology, 10(9), 1430-1436, 2016.
[8] C. Denkert, S. Wienert, A. Poterie, et al. Standardized evaluation of tumor-infiltrating
lymphocytes in breast cancer: results of the ring studies of the international immuno-
oncology biomarker working group. Modern Pathology, 29(10), 1155-1164, 2016.
Communication
Conference talks
[1] A. Poterie. Decision trees and random forests for grouped variables. 50ème Journeées
de Statistiques. Saclay (France), 2018.
[2] A. Poterie. Classification tree for grouped variables. 49ème Journeées de Statistiques.
Avignon (France), 2017.
[3] A. Poterie. Estimation de l’efficacité et de la toxicité des traitements chez les patients
inclus dans des essais de phase I : apport des méthodes reposant sur le score de
propension. EPICLIN. Montpellier (France), 2015.
[4] A. Poterie. Performances of methods based on propensity score in phase I trials
databases - Evaluation of molecular oriented metastatic breast cancer drugs. Journée
nationale biopharmacie et santé, SFdS. Paris (France), 2014.
[5] A. Poterie. Performances of methods based on propensity score in phase I trials
databases - Evaluation of molecular oriented metastatic breast cancer drugs. GDR
Statistiques et Santé. Paris (France), 2014.
Seminar and workshop talks
[6] A. Poterie. Arbres de décision et forêts aléatoires pour variables groupées. ViCBiostat
Work In Progress. Melbourne (Australia),2019.
[7] A. Poterie. Arbres de décision et forêts aléatoires pour variables groupées. Séminaire
de l’équipe de Probabilités et Statistique, Laboratoire Dieudonné, Université de Nice.
Nice (France), 2018.
[8] A. Poterie. Arbres de classification pour variables groupées. Septième Journée des
Jeunes Statisticiens, SFDS. Porquerolles (France), 2017.
[9] A. Poterie. Arbres de décision pour les variables groupées. Séminaire de Statistique
de l’IRMAR. Rennes (France), 2016.
Workshop/Summer Schools attended
02/2019—- ViCBiostat Summer School 2019, VICBiostat, Melbourne (Australia).
08/2017—- Eight Montreal Industrial Problem Solving Workshops, Centre de recherches
en Mathématiques de l’Université de Montréal, AMIES. Montreal (Canada).
04/2017—- Septième Journée des Jeunes Statisticiens, SFDS. Porquerolles (France).
01/2016—- Semaine Maths-Entreprises, AMIES. INRIA Antibes (France).
Award and Scholarship
2015 – 2018 Ministère de l’Enseignement Supérieur et de la Recherche, Research scholar-
ship of 68 811,96e.
2017———- AMIES, Mobility Grant of 1704,70e.
2015
2016———- AMIES, Mobility Grant of 500e.
20152013 – 2014 GENES, Merit-based grant of 800e.
2012 – 2013 GENES, Merit-based grant of 1600e.
Professional Organizations
2016 – 2018 Organizer of the PhD student seminar. IRMAR,Rennes (France).
2016 – 2018 Member of the Doctoral School Council. IRMAR,Rennes (France).
2012 – 2014 Member of ENSAI Junior Consultant (EJC). ENSAI, Rennes (France).
Languages
French: Mother tongue.
English: Advanced, IELTS: 7/9 (06/2018), TOEIC: 850/990, (01/2013).
Computer Skills
Statistical Packages: R, SAS, STATA, SPAD, WInbugs.
Languages: C/C++, Java, Python, SQL.
Applications: LATEX, Microsoft Office.
Operating Systems: Linux, Mac OS, Windows.
Activities and Interests
Running: Member of the Athletic Club Cessonnais.
Diving: Level 1 FFESSM.
Travel: Australia, Canada, England, Ireland, Portugal, Malta, Morocco, New-Zealand,
Italy, Vietnam, French Guiana.You can also read
