Sept 2020, After having been a Professor of Statistics at Ecole Polytechnique and a visiting researcher at Google Brain IA Paris, I have a new position of Advanced Researcher at Inria. I  am a scientific collaborator associated to CMAP Polytechnique and teaching at Ecole Polytechnique, in particular causal inference.
News: Workshop 22-23 June 2021. Leveraging observational data with ML.

– Talk: Supervised learning with missing values (pres of linear models, random forest, neural networks) slides, videos
– Talk: Causal inference with missing values slides, videos
– Talk: A  missing values tour  slides, video available (start at 30′)
Interns/Phd/Postdoc positions on causal inference and policy learning for personalized medicine. Contact me. Internship to predict the need of intubation available.

Project TrauMatrix decision tool for intensive Care; short VideoPodcast 
– ICUBAM ICU Bed Availability Monitoring  in the Grand Est région during the COVID-19 epidemic. Fork.
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R-mis-static website, with missing values ressources (lecture, workflows, tutorials, etc.), Contribute!
Rforwards dedicated to widen the participation of the minorities in communities.

julie.josse[at]inria.fr   – Office, 226,  INRIA Montpellier. Member of IDESP.

My main research fields are: missing values (EM algorithms, imputation, supervised learning), causal inference (treatment effect estimation, combining RCT and observational data; survival analysis),  visualization with dimensionality reduction (PCA, correspondence analysis), questionnaire analyses, multi­-blocks data; low rank matrix estimation; main application in  health for personalised medicine.  Detailed CV