Jann started his journey as a quant. economist in Heidelberg. Thrilled by its manifold opportunities, he then entered the data science train via his master’s in stats at LMU Munich. He applied various stats-related techniques (glms, survival analysis, deep learning, traditional machine learning) on various data types (sensor, text, imagery, tabular) in various settings (industry, research, startup) and is still excited by the multitude of use cases for sophisticated data science solutions. Since spring 2019 he is a PhD student within Bernd Bischl’s Computational Statistics Group at LMU, applying his skills within the Fraunhofer IIS ADA Lovelace Center. Jann’s research is centered around the problem of learning from few labeled data with applications to functional/ time series data.