Ruben Seyer

PhD candidate in applied mathematical statistics

I am currently pursuing my PhD under the supervision of Moritz Schauer and Aila Särkkä at the Dept. of Mathematical Sciences, Chalmers/University of Gothenburg.

My interests lie at the intersection of Bayesian inference and machine learning, where we develop computational methods for statistics. I am particularly interested in applications to spatial statistics and point processes. My work so far concerns applying stochastic gradient methods to MCMC and piecewise deterministic Markov processes, automatically turning Monte Carlo samplers into Monte Carlo gradient samplers.

I graduated MScEng (civilingenjör) from Chalmers in 2023 on a thesis about differentiable Monte Carlo methods using piecewise deterministic Markov processes. During my studies I produced a substantial amount of notes which many students still find useful.