My academic research focuses on statistical machine learning for data problems from various domains, especially, in the field of bio-medicine, genetics, and natural sciences more generally. In particular, I study problems for tree ensemble methods, such as random forest, blind source separation with certain finite alphabet constraints, change-point detection employing multiscale methods, and statistical methodology related to tree structures.<\/p>\n\n\n\n
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| Since October 2022<\/td> | Professor for Machine Learning, Faculty of Informatics and Data Science, University of Regensburg, Germany<\/td>\n<\/tr>\n |
| Dec 2020 - Sep 2022<\/td> | Scientific Expert at Bayer AG, \nResearch & Development, Pharmaceuticals, Leverkusen, Germany<\/td>\n<\/tr>\n |
| July 2019 - Nov 2020<\/td> | Postdoc, \nResearch fellowship German Research Foundation (DFG), \nDepartment of Statistics, \nUniversity of California, Berkeley, USA<\/td>\n<\/tr>\n |
| Aug 2018 - June 2019<\/td> | Neyman Visiting Assistant Professor, \nDepartment of Statistics, \nUniversity of California, Berkeley, USA<\/td>\n<\/tr>\n |
| Jan - Aug \n2018<\/td> | Postdoc, \nDFG - Research Training Group 2088, Discovering structure in complex data: Statistics meets Optimization and Inverse Problems, University of Goettingen, Germany<\/td>\n<\/tr>\n |
| 2014 - 2017<\/td> | PhD student, \nInstitute for Mathematical Stochastics, \nUniversity of Goettingen, Germany \n(PhD Supervisor: Professor Axel Munk)<\/td>\n<\/tr>\n |
| 2009 - 2014<\/td> | Studies of mathematics, \nUniversity Goettingen (Germany) and \nUniversity of Edinburgh (UK)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n\n In this YouTube video I give an overview of my PhD thesis for non-experts at the 3-Minute Thesis Competition, University of Goettingen:<\/p>\n\n\n\n |