Ruben Seyer
PhD candidate in 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.
We work at the intersection of Bayesian inference and machine learning, where we develop computational methods for statistics. I am interested in Markov Monte Carlo methods and applications to spatial statistics and point processes. Among other things, my research concerns designing non-reversible samplers, and applying stochastic gradient methods to MCMC or piecewise deterministic Markov processes to automatically turn samplers into 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.