I am interested in the development of methods for extracting relevant information from data. This data are complex and often arise from collaborations with lab scientists. My research in mathematical statistics is concerned with tools to equip such methods with statistical error control. The challenge is to make them computationally feasonable at the same hand.
Statistical inverse problems, nonparametric regression, statistical imaging and signal recovery, multiscale testing and estimation, qualitative inference, shape analysis, optimal transport.
fast segmentation algorithms, motion estimation, resampling
Statistical methods for single molecule experiments, ion channel recordings, nanoscale fluorescence microscopy. My work on Nanostatistics has been highlighted in the Research Features Magazine.
- Other areas of application I have been involved include
Clinical trials: Bioequivalence and noninferiority trials.
Econometrics: microstructure noise models.
Pattern recognition: Analysis of fingerprints.