New Technologies, Innovation, Artificial Intelligence (AI)

I’m the head of computational biology at DNTOX GmbH and postdoctoral researcher at the Leibniz Research Institute for Environmental Medicine (IUF). We're on a mission to develop test methods for animal-free screening of chemicals, regarding their potential to disturb brain development and cause developmental neurotoxicity (DNT). I'm also collaborating with the Bioinformatics working group of Prof. Dr. Axel Mosig at Ruhr University Bochum, Department of Biophysics, where I supervise work on applications of deep learning to biomedical image analysis and computational biostatistics.

Before joining IUF, I was a PhD student and PostDoc in the Algebra working group of Prof. Dr. Markus Reineke at Ruhr University Bochum, where I worked on geometric approaches to linear algebra type classification problems.We studied geometric properties of quiver moduli spaces with topological, arithmetic, algebraic, and homological methods.

My work is driven by the goal of replicating human learning and inferencing in machines, including their weak points, such as bias. I use mathematical models, computer simulations, and behavioral experiments to investigate the principles that guide people on a daily basis, such as inductive reasoning.

Besides empirical methods such as behavioral testing of adults, I approach these principles by Alexander Grothendieck’s "Rising sea" philosophy. The long and short of it: “If a phenomenon seems hard to explain, it’s because you haven’t fully understood how general it is. Once you figure out how general it is, the explanation will stare you in the face.” One thing that always excited me about Grothendieck's geometry revolution was that he rethought (and eventually redefined) the very notion of a point in geometry. Strongly inspired and influenced by this, I have generalized the very notion of symmetry (and rethought the classification problem) in On the ambiguity in classification, 2023, and demonstrated first applications in computational cognitive science in Discovering latent causes and memory modification: A computational approach using symmetry and geometry, 2023.