Nice to meet you!
My name is Sebastian, and I’m a Computer Scientist currently working as a Postdoctoral Fellow at Linnaeus University, a position I began in January 2025.
I completed my PhD in February 2025 at the Paris Lodron University of Salzburg, Austria, under the supervision of Roland Kwitt. My doctoral research was rooted in topological data science and Bayesian inference, with a particular focus on applying tools from stochastic analysis and manifold learning to problems in time series analysis.
In recent years, (deep) neural networks have demonstrated remarkable success in solving complex tasks by learning from vast amounts of data. Yet, despite their impressive performance, the reasons behind their success often remain poorly understood.
I believe that extracting meaningful knowledge from data hinges on two key components:
1.A deep understanding of the structure of the data, and
2. Insight into how models learn and process this structure.
My current research is motivated by the desire to study this interaction from a mathematical perspective—with the ultimate goal of understanding how we learn from data. I’m convinced that mathematics is the language of choice for bringing clarity to these fundamental questions.