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 Video, Podcast
– ICUBAM ICU Bed Availability Monitoring in the Grand Est région during the COVID-19 epidemic. Fork.
– 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