Languages spoken: French (native), English (fluent), German (conversational)

Research Experience

2013—current: Researcher
ARMINES/Mines ParisTech, Institut Curie and INSERM, Paris (France)
Centre for Computational Biology

2011—2013: Research Scientist
Max Planck Institutes, Tübingen (Germany)
Machine Learning and Computational Biology research group, headed by Karsten Borgwardt
Statistical methods and machine learning for GWAS analysis, epistasis detection, disease gene prediction.

2009: Summer Research Intern
IBM R&D Labs Tel-Aviv (Israel)
Statistical analysis of SNP data for the HyperGenes project, under the direction of Michal Rosen-Zvi.

2005—2010: Graduate Student Researcher
UC Irvine, Irvine, CA (United States)
Advisor: Pierre Baldi
Prediction of molecular properties (kernel methods), virtual high-throughput screening (kernel methods, neural networks), prediction of chemical reactions, docking.

2005: MSc Research Intern
Ecole des Mines de Paris, Fontainebleau (France)
Advisor: Jean-Philippe Vert
Implementation and validation of kernels for protein sequences, web interface for kernel testing.

Teaching Experience

Online lectures

Data Scientist path at OpenClassrooms.

Lecturer

2014—2018 Mines ParisTech (France)
Génomique et bionformatique : une introduction

2015—2018 Centrale Paris (France)
Foundations of Machine Learning

2017—2017 Mines ParisTech (France)
Large Scale Machine Learning

2012—2013 Eberhard Karls Universität Tübingen (Germany)
Data Mining in der Bioinformatik (2012, 2013)

Teaching Assistant

2012—2013 Eberhard Karls Universität Tübingen (Germany)
Seminar Bioinformatik (2012 , 2013)

2006—2008 UC Irvine, Irvine, CA (United States)
Introduction to Probabilities and Statistics for Computer Science (2008)
Introduction to Artificial Intelligence (2006)

Student Supervision

2018 Weiyi Zhang, Convolutional neural networks for multiplex biological nework (M1, joint supervision with Antonio Rausell at Institut Imagine)

2018 Victor Sorreau. Machine learning and prediction of variant-induced RNA splicing defects (L3, joint supervision with Alexandra Martins at UFR Médecine et Pharmacie, Rouen.)

2018 Liyang Sun. Convolutional neural networks for protein representation (Projet Innovation at CentraleSupelec, joint supervision with Benoît Playe at MINES ParisTech.)

2017 Adrien Galamez, Paul Magon de la Villehuchet, Olivier Pham and Manon Revel. Identifying recurrence in electronic health records (Projet Innovation at CentraleSupelec, joint supervision with Jean-Philippe Vert at MINES ParisTech and Julien Guérin at Institut Curie

2016—current Lotfi Slim, Detection of epistasis in genome-wide association studies with machine learning methods for biomarkers and therapeutic target identification (PhD, joint supervision with Jean-Philippe Vert at MINES ParisTech and Clément Chatelain at Sanofi)

2016—current Héctor Climente González, Integrating structural constraints in multi-locus genome-wide association studies (PhD, joint supervision with Véronique Stoven)

2016—current Christophe Le Priol, Systemic analysis of the micro-RNAs involved in epithelial cancers (PhD, joint supervision with Xavier Gidrol at CEA Grenoble).

2016 Athénaïs Vaginay, Multi-phenotype identification of biomarkers in a biological network (BiB Paris-Diderot Intern)

2014—2017 Vìctor Bellòn, Adverse drug reaction discovery (PhD, joint supervision with Véronique Stoven at MINES ParisTech)

2015 Killian Poulaud, Multitask feature selection in a graph (Supinfo Intern)

2014 Jean-Daniel Granet, Development and parallelization of the SConES tool for graph-guided GWAS (42 Intern)

2013—2014 Udo Gieraths, Machine Learning for identification of autosomal recessive genomic variants (MSc, joint supervision with Karsten Borgwardt and Hilal Kazan, Eberhard Karls Universität Tübingen)

2012—2013 Fabian Aicheler, Improving the functional annotation of genomic variants via machine learning (MSc, joint supervision with Karsten Borgwardt, Eberhard Karls Universität Tübingen)

2011—2012 Valeri Velkov, Mining correlated loci at a genome-wide scale (MSc, joint supervision with Karsten Borgwardt, Eberhard Karls Universität Tübingen)

Education

2010: PhD in Computer Science
UC Irvine, Irvine, CA (United States)
Advisor: Pierre Baldi
Statistical data mining and machine learning for chemoinformatics and drug discovery

2005: MSc in Mathematics and Computer Science
ENST Bretagne (now IMT Atlantique) (France)
Specialization: Software and Formal Methods

2005: Master of Engineering
ENST Bretagne (now IMT Atlantique) (France)
Specialization: Computer Science for Telecommunications

Scholarships & Awards

2014: Second-best performing team
Phase I of the DREAM 8.5 Rheumatoid Arthritis Responder Challenge

2013: Second-best performing team
Subchallenge 2 of the DREAM 8 NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge

July 2013: Travel fellowship from ISCB to attend ISMB 2013.

June 2013: Travel fellowship from JOBIM 2013 to attend the conference.

July 2012: Young researcher participant of the Lindau Nobel Laureate Meeting.

2011—2013: Alexander von Humboldt Research Fellowship.

2009—2010: IBM PhD Fellowship.

2009: CINF-Symyx Scholarship for Scientific Excellence.

2008—2010: Honorary Pre-Doctoral Trainee
Biomedical Informatics Training Program
UC Irvine Institute for Genomics and Bioinformatics .

2007: First Prize and Invited Presentation
Agnostic Learning vs. Prior Knowledge Challenge at IJCNN 2007 (HIVA dataset).

2006: UC Irvine School of Information and Computer Science Scholarship
to attend the Grace Hopper Celebration for Women in Computing.

2005—2009: Ted & Janice Smith Graduate Fellowship.

Professional Services

Meetings organized

MLSB 2017 at ISMB 2017
Idea DREAM Challenge 2016–2017
FEAST Workshop (Features and Structures) at ICML 2015
MLPM Summer School 2014 (Machine Learning in Personalized Medicine)
MLPM Summer School 2013 (Machine Learning in Personalized Medicine)

PhD thesis committees

Yunlong Jiao, Rank-based Molecular Prognosis and Network-guided Biomarker Discovery for Breast Cance, PSL Mines ParisTech.
Flore Harlé, Multiple change-point detection in multivariate time series: application to the inference of dependency networks, Grenoble Alpes.

Recruitment committees

Jury d'admissibilité MCF, ENSIMAG 2018
Jury d'admissibilité CR2 & CR1, Inria Bordeaux — Sud-Ouest 2016.

Reviews and Program Committees

Referee: AOAS, BMC Bioinformatics, Bioinformatics, IJCV, JCIM, Journal of Chemoinformatics, JMLR, KAIS, Molecular Biosystems, Nature Genetics, Neural Networks, New Journal of Chemistry, IEEE TCBB, IEEE TPAMI.

More on my Publons profile.

Nowadays I only review for RoMEO green journals.

I'm also a member of the F1000 Prime "Bioinformatics, Biomedical Informatics & Computational Biology" Faculty, under the Cataloguing & Benchmarking Computational Methods Section. I was June 2017's featured Faculty Member of the Month.

Conference reviewer: BCB (2017) ECML/PKDD (2013, 2014, 2015); CD-MAKE(2017); CAp (2018); ICML (2013, 2015, 2017], 2018); JOBIM (2018); KDD (2016); MLCB (2014); MOD (2015, 2016, 2017); NIPS (2013, 2014, 2017); PSB-PM (2015, 2016, 2018); SciPy (2015, 2018); SIMBAD (2015); WIML (2017).

Area chair: NIPS 2016, WiML 2017.

Reviewer for funding agencies: ANR (France), BSF (US-Israel), CQDM (Canada), FWO (Belgium), Mitacs (Canada).

Outreach

2018 Jury in a young mathematicians tournament TFJM² Strasbourg, TFJM² National.

2017 Cofounder of the Paris branch of Women in Machine Learning and Data Science.

2017 Jury in a young mathematicians tournament TFJM Strasbourg.

2014 Participated in a Woman in Mathematics awareness day (targeted towards high-schoolers), « Filles et maths : une équation lumineuse ».

Media

2018-02-07, L'Usine Nouvelle : Le machine learning dans les gènes
2018-01-30, Fractales : Chloé-Agathe Azencott, décoder les gènes

Successful Applications

Candidature au poste de Maître-assistant de classe normale en Science des données (2018) ]]Dossier|http://cazencott.info/dotclear/public/candidacies/2018-05-25_azencott.pdf]]

Qualification aux fonctions de maître de conférence (2013)
[Dossier] [Annexe (Section 26)] [Annexe (Section 27)]