Sept 2016, I am a professor of Statistics at the applied math department (CMAP) at Ecole Polytechnique (Saclay) and member of the data-science initiative and XPOP INRIA team.

News:  elected at the R Foundation for Statistical Computing and in the Conference Committee.  Member of R forwards.  Head of the communication of the French Statistical Society.
Blog posts and multivariate studies of the R community. Blog posts: Multiple imputations;  Can we believe in the  imputation?

PostDoc Positions/ internships/ engineer  available on missing values.  Interested contact me.  
julie.josse[at]polytechnique.edu   – Office, Labo 0,  CMAP 3rd floor num: 05 3003

My main research fields are missing values, visualization with dimensionality reduction (PCA, correspondence analysis), multi­-blocks data, low rank matrix estimation, questionnaire analyses. Detailed CV

Research

On going projects:

Associate Editor: Journal of Computational & Graphical Statistics.

An overview of my research can be found in my Habilitation.  (slides)

Publications:
YearAuthors Title link
2018Josse, J., Husson, F. Robin, G. and Balasubramanian. N.Imputation of mixed data with multilevel SVD.pdf
2018Jiang, W., Lavielle, M. and Josse, J. Stochastic approximation EM for logistic regression with missing values.pdf
2017Holmes, S and Josse, J.50 years of data-sciences, discussion.
Journal of Computational and Graphical Statistics JCGS.
pdf
2017Bollmann, S., Cook, Di. Dumas, J., Fox, J., Josse, J., Keyes, O. Strobl, C., Turner, H. and Debelak, R.A First Survey on the Diversity of the R Community.
R journal.
2017G. Celeux, J. Jewson, J. Josse, J.M. Marin and C. P. Robert.Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig.

pdf
2017-2018Josse, J. and Reiter, J.P.Introduction to the Special Section on Missing
Data.
Statistical Science
2017Robin, G, Sardy, S., Moulines, E. and Josse, J. Low rank log-linear models for contingency tables.
Submitted in Biometrika
pdf
2017Mozharovskyi, P., Husson, F. and Josse, J.Nonparametric imputation by data depth.
In revision in JASA.
pdf
2017Foulley, JL, Celeux, G and Josse, J.Empirical Bayes approaches to PageRank type
algorithms for rating scientific journals.
Technical report.
pdf
2016Sobczyk, P, Bogdan, M. and Josse, J.PCA using penalized semi-integrated likelihood.
Journal of Computational and Graphical Statistics JCGS.
pdf
2016Fithian, W. and Josse, J.Multiple Correspondence Analysis & the Multilogit Bilinear Model.
Journal of Multivariate Analysis.
pdf
2016Husson, F., Josse, J. and Saporta, G.Jan de Leeuw and the French school of data analysis.
Journal of Statistical Software.
pdf
2016Josse, J., Sardy, S. and Wager, S.denoiseR: a package for low rank matrix estimation.
In revision in JSS.
pdf
2016Groenen, P. and Josse, J.
Multinomial Multiple Correspondence Analysis. pdf
2016Fujii, H., Josse, J., Tanioka, M., Miyachi, Y. Husson, F., and Ono, M.Regulatory T cells in melanoma revisited by a computational clustering of FOXP3+ T cell subpopulations.
Journal of Immunology.
pdf
2015Audigier, V., Husson, F. and Josse, J.MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis.
Statistics and Computing.
pdf
2015-2016Josse, J and Wager, S.Regularization for Low-Rank Matrix Estimation.
Journal of Machine Learning research.
pdf
2015Josse, J. and Sardy, S.Adaptive Shrinkage of singular values.
Statistics and Computing.
pdf
2015Josse, J and Husson, F.
missMDA a package to handle missing values in and with multivariate data analysis methods.
Journal of Statistical Software.
pdf
2015 Audigier, V., Husson, F. and Josse, J.Multiple Imputation with Bayesian PCA. 
Journal of Statistical Computation and Simulation.
pdf
2015-2016Josse, J. and Holmes, S.Measuring multivariate association.
Statistics Survey.
pdf
2014Audigier, V., Husson, F. and Josse, J.A principal components method to impute mixed data. 
Advances in Data analysis and Classification. 
pdf
2014Josse, J., Wager, S. and Husson, F.

Confidence areas for fixed-effects PCA. 
Journal of Computational and Graphical Statistics.
pdf
2014Dray, S and Josse, J.Principal component analysis with missing values: a comparative survey of methods.
Plant Ecology. 
pdf
2014Josse, J.,  van Eeuwijk, F., Piepho, H-P and Denis, J.B.Another look at Bayesian analysis of AMMI models for genotype-environment data. 
Journal of Agricultural, Biological, and Environmental Statistics.
pdf
2013Verbanck, M., Josse, J. and Husson, F.Regularized PCA to denoise and visualise data. 
Statistics and Computing.  
pdf
2013Josse, J., Timmerman, M.E. and Kiers, H.A.L.
Missing values in multi-level simultaneous component analysis.
Chemometrics and Intelligent Laboratory Systems.
pdf
2013Husson, F. and Josse, J.Handling missing values in Multiple Factor Analysis.
Food Quality and Preferences.
pdf
2013Josse, J and Husson, F.Handling missing values in exploratory multivariate data analysis methods.
Journal de la SFdS. Paper written for the best Ph.D doctoral thesis prize delivered by the French Statistical Society.
pdf
2012Josse, J., Chavent, M., Liquet, B. and Husson, F.
Regularized Iterative Multiple Correspondence Analysis.
Journal of Classification.
pdf
2011Josse, J and Husson, F.Selecting the number of components in PCA using cross-validation approximations.
Computational Statistics and Data Analysis.
pdf
2011Josse, J., Husson, F. and Pagès, J.Multiple imputation in PCA.
Advances in data analysis and classification.
pdf
2010Josse, J., Husson, F. and Pagès, J.Principal component methods - hierarchical clustering - partitional clustering: why would we need to choose for visualizing data?
Technical report.
pdf
2009Josse, J., Husson, F. and Pagès, J.Analyse en Composantes Principales.
Journal de la SFdS.
pdf
2008Josse, J., Husson, F. and Pagès, J.Testing the significance of the RV coefficient.
Computational Statistics and Data Analysis.
pdf
2008Lê S., Josse, J. and Husson, F.FactoMineR: an R package for multivariate analysis.
Journal of Statistical Software.
pdf

Books

P-A. Cornillon, A. Guyader, F. Husson, N. Jégou, J. Josse, M. Kloareg, E. Matzner-Løber, L. Rouvière. (2012). R for statistics. Chapman & Hall.

P-A. Cornillon, A. Guyader, F. Husson, N. Jégou, J. Josse, M. Kloareg, E. Matzner-Løber, L. Rouvière. (2008, 2010, 2012). Statistique avec R. Presses Universitaires de Rennes.

Chapter in Books:
Husson, F. & Josse, J. (2014). Multiple correspondence analysis. Book chapter. The Visualization and Verbalization of Data

Talks

Selected Talks:
MultiLogit bilinear model & MCA
Bootstrap approach for low rank estimation
A missing values tour with principal components
Visualization with regularized PCA and confidence ellipses
Exploratory data analysis: multi­-blocks/3ways methods
Multiple imputation for categorical data
Imputation of mixed data: Random forest/PCA

All the talks:

YearTitle EventSlides/Video
2018Distributed multilevel matrix completion for medical dataFrance-Finland Worshop
pdf
2017Stochastic Approximation EM for logistic regression with missing valuesCMStat, London, 17 Decemberpdf
2017Single Imputation with data depthCMStat, London, 17 Decemberpdf
2017 R forwards to widen the participation of under-represented groupsuseR!2017, 7 Julyvideo
pdf
2017Empirical Bayes approaches to PageRank type algorithms for rating scienti fic journals French Stat Society, 29 Maypdf
2017Low-rank log-linear models. Vienna, University of economics and business, 16 March
Telecom, Paris, 23 March.
pdf
2016 Meetup Machine Learning, Paris, France, 10 February
2016 Imputation with data depth - Pavlo Mozharovskyi French Stat Society, Montpellier, France, May pdf
2016MultiLogit bilinear model & MCA Working group on model based clustering, Paris, France, 22 July
AgroPariTech, Paris, France, 13 June
2015Missing values and principal components methods INRIA, Orsay, France, 12 October
Tesla Motor, Palo Alto, USA, 14 August
2015Multiple imputation for categorical data Conference CARME (correspondence analysis & related methods), Napoli, Italy, 21 September
Journée de Statistiques, Rennes, France, 23 october
20152015 A flexible framework for regularized low rank matrix estimationLos Alamos, USA, 15 February
Rotterdam University , Netherlands, 30 January
Adobe Research , San Jose, USA, 20 January
2015 Visualization with regularized PCA Stanford Biostatistics, Palo Alto, USA, 15 January
2014A flexible framework for regularized low rank matrix estimation Montpellier 2 University, France, 20 October
Paris Descartes University, France, 24 October
Wroclaw University, Poland, 31 October

details.

Software – R community

I am involved in the R software community and I am sincerely glad to have been elected as a member of the R Foundation for Statistical Computing,

Development of packages:
FactoMineR: visualization with principal components methods
missMDA: missing values (imputation continuous, categorical data) – matrix completion
denoiseR: low rank matrix estimation with regularized SVD and bootstrap

I  served as an associate editor of Journal of Statistical Software (2011-2017) and I am involved in Rforwards to leading the R community forwards in widening the participation of women and other under-represented group.
With M. Chavent, S. Dray, R. Genuer, F.Husson, B. Liquet, J. Sarracco, we created the « French R board group » to support the organization of Les Rencontres R.

News: Video presentation of Rforwards. Blog posts and multivariate studies of the R community. Member of the scientific committee of Les rencontres R, useR! 2017.

Support R with the R consortium.

Teaching

As a French associate professor, I teach around 200 hours/year (lectures, computer labs mainly with the R software) and I supervise master students projects and their internship in industry. Learn more

In addition, I give tutorials in different instituts and in conferences:

YearTitleEventsslides/video
2016-2017Missing values imputationuseR!2016, Stanford
Gdr Ecology stat, Lyon
INRIA, saclay
Ozone data
codeMissUSER2016
slides
Lab
Notes
2015Handling missing values with a special focus on the use of principal component methods. (3h).useR! 2015, the R useR conference, Aalborg, Denmark
2014Lecture on dealing with missing values. (3h)Stanford University, CA, USA[slides] [ozone data]
[code]
[ecological data]
[code]
2011Panorama sur les méthodes d'analyse exploratoire des données. (3h)Journées de l'Ecole Doctorale Pierre Louis de Santé Publique : Epidémiologie et Sciences de l'Information Biomédicale. St Malo, France[slides, data]

Bio

Her first employment was in the statistics departement of an Agronomy University (Agrocampus Ouest) where she was trained to « the French data analysis school » and had the opportunity to work closely with researchers from other departments and increases her interest in transversal studies. In the meantime, she prepared her PhD which was rewarded by the French Statistical Society as the best PhD in applied statistics. She has specialized in missing data, visualization and the nonparametric analyses of complex data structures. Her work was rewarded by a European Union grant in 2013 to increase her research potential and to spend a year at Stanford University. She spent a year as a researcher in INRIA before joining Polytechnique in 2016. At Polytechnique, she is actually responsible of a master data-sciences for business in collaboration with HEC. She has published over 30 articles and written 2 books in applied statistics. Her experience on dealing with incomplete data is recognized by the community: she organized the MissData conference on missing value in 2015 and she is often invited to give lectures to share her experience. Her vocation is to push methodological innovation to bring useful application of her research to the user in particular in bio-sciences and health. Julie Josse is dedicated to reproducible research with the R statistical software: she has developed packages including FactoMineR, denoiseR, missMDA to transfer her work, she is a member of the R foundation and of Rforwards to increase the participation of minorities in the community.

Misc

Conferences organization head:
– The first MissData on missing values and matrix completion, June 2015.
– Correspondence analysis related methods CARME 2011. Videos. Let the data speak…. data analysis
– The R conference useR! 2009

Links:
– SFdS French Statistical Society – Interested in data sciences? Join-us!!
– Some references on data analysis, data sciences.
– These days I am a fan of Brian Caffo youtube channel.
– Support  eR-Biostat to make material available and help some countries.