About Me
I am currently finishing my PhD in Statistics at LMU Munich advised by Prof. Bernd Bischl expecting to graduate in the fall of 2022.
The goal of my research is to facilitate access to machine learning methods to a broader audience including domain experts and citizen data scientists. I hope to contribute to this goal via my research in machine learning, AutoML, algorithmic fairness and benchmarking. I also enjoy developing and contributing to Open Source software mainly in R.
Background
Prior to starting my PhD I completed a B.Sc. as well as a M.Sc. in Statistics at LMU Munich with two exchanges at Universidad Complutense de Madrid and Universitat Politècnica de Catalunya (Barcelona).
Throughout my studies I worked part time at several companies such as Telefónica Germany where I worked on automated quality control for data bases, risk scoring and text analytics. During my master’s thesis at the Bosch Center for Artificial Intelligence (BCAI) I worked on a method for anomaly detection in time-series data. Before finishing my degree, I interned at Telefónica Alpha in Barcelona working on a moonshot project related to mental health and personal wellbeing. During my PhD I interned with Roche Pharma in personalised healthcare working on domain generalization for clinical survival models.
During my PhD i furthermore freelanced in several capacities, e.g. holding programming courses and machine learning / deep learning courses at several DAX companies but also applied machine learning/computer vision projects.
Teaching
I am currently teaching the Innovation Lab Big Data Science where I supervise student groups on machine learning and data science software development projects provided by companies, NGO’s and research institutions.
Curriculum Vitae
An up-to-date version of my CV can be downloaded here.