The school is aimed at young researchers (PhD students and early postdocs) and practicioners alike and offers an excellent opportunity to learn about recent and important developments in mathematical statistics directly from leaders in their respective fields. The following three courses will be offered (see courses for full details):
- Geometry of convex cones with applications to high-dimensional statistics
Zakhar Kablucho, University of Münster
- Principal Component Analysis: some recent results and applications
Karim Lounici (CMAP-Ecole Polytechnique)
- Statistical inference of incomplete data models to analyse ecological networks
Stéphane Robin (AgroParisTech/INRA/univ. Paris Saclay & Muséum National d’Histoire Naturelle)
Local organizers are Yannick Baraud and Simon Campese.
summer school dates: 29.6.-3.7.
registration deadline: 15.6.
financial support application deadline: 15.5.
The “ERA Chair in Mathematical Statistics and Data Science – SanDAL” is a prestigious grant awarded to the University of Luxembourg by the Era Chairs under the EU’s Horizon 2020 framework programme. With a budget of 2.5 million euros for the period 2019-2024, the university will create a high-level research group in mathematical statistics and data science. Chair holder is Prof. Yannick Baraud.
The project will boost research and training in mathematical statistics and data science. The ERA Chair research activities will focus on two areas: “High-Dimensional Data Analysis” to have a deeper understanding of emerging computational tools and “New Mathematical Tools for Contemporary Statistics” to develop new and more sophisticated statistical methods. In addition, new teaching programmes at Master and PhD levels will be elaborated to provide future students with the necessary skills in mathematical statistics and data science to understand, develop and apply new tools in various fields.
More details about the chair can be found on the dedicated webpage.
SanDAL has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 811017.