Measurement techniques to characterize the properties of materials, such as photoemission spectroscopy, were continuously improved throughout the last decades. This led to a drastic increase of the measured data in terms of size, resolution, and complexity. Analyzing those dataset poses challenges, e.g. processing them in an efficient manner and extracting physically meaningful and relevant parameter. In my PhD, I want to tackle them by using and extending existing machine learning models and developing new approaches.