**Resarch
Group in Mathematical Statistics**

**`Uncertainty
Quantification and Modern Statistical Inference (UQMSI)'**

Our research group investigates the mathematical underpinnings of modern statistical inference problems, with a particular focus on uncertainty quantification methodology (such as confidence statements and tests) in high- and infinite dimensional models. The mathematics involved lies at the intersection of theoretical statistics, probability theory and functional analysis. Currently (2015-2020) we are supported by a Consolidator Grant of the European Research Council (ERC).

NEWS: June 2017 Workshop on Statistical foundations of uncertainty quantification for inverse problems

Research topics include:

*nonparametric statistics**confidence regions for high-dimensional statistical models**Bayesian nonparametrics**statistics for stochastic processes and inverse problems**concentration of measure and empirical process theory*

*Current
group members:*

*Former
group members:*

Postdocs: A. Carpentier, K. Lounici, J. Soehl, B. Sriperumpudur

Phd students: A. Bull, A. Kueh, K. Ray

Past activities:

2017 YES VIII Workshop on Uncertainty Quantification

Course on Concentration Inequalities by Stephane Boucheron

2015 Oberwolfach Workshop Probabilistic Techniques in Modern Statistics