Hey, I'm David and I'm a mathematician with a focus on stochastics, statistics, and statistical learning, working at the intersection of probability theory and applied machine learning, with an interest in AI safety and interpretability.

I hold two Bachelor's degrees and a Master's:

• Bachelor's in Mathematics — thesis on MCMC methods (Metropolis-Hastings, Gibbs sampling, slice sampling) for inference in Hidden Markov Models.
• Bachelor's in Psychology — agent-based modeling of behavioral phenomena; this is where my interest in how humans (and by extension, learned agents) reason about incentives and reward comes from.
• Master's in Mathematics, focused on stochastics/statistics — thesis on multivariate Kolmogorov-Smirnov goodness-of-fit tests. I write Python for research and simulation. So far I've worked on goodness-of-fit testing, empirical process theory, and high-dimensional statistics, and I'm increasingly drawn toward AI safety, interpretability, and alignment.

Some of my projects are pinned below or in my public repositories.

Feel free to contact me if you have any questions: david.hamann@posteo.de