Kris Dreher received his MSc degree in Physics from the University of Heidelberg in 2020. He is currently pursuing a PhD in the field of applied data science and photoacoustic imaging (PAI), specifically focussing on deep learning-based domain adaptation methods to tackle the inverse problems of photoacoustic imaging. He is also an active member of the data management theme of the international photoacoustic standardisation consortium (IPASC) where he tries to develop open source software and framework for validation of computational methods in PAI.
In his free time, Kris enjoys meeting up with friends, playing all sorts of sports (football, tennis, skiing, ...) and everything that has something to do with comedy.
Expertise
- Simulations, especially Monte Carlo methods
- (Invertible) neural networks with focus on unsupervised domain adaptation methods
- Open source software development
- Medical imaging
Links