My research designs Bayesian inference and probabilistic programming to build systems that are explicit and reliable in their representation of uncertainty. Specifically, I focus on variational inference methods for filtering and mixture modeling in real-time, non-Gaussian settings.

I am a DDSA Fellow and postdoctoral researcher in the SQUARE group at the IT University of Copenhagen. I completed my PhD with Thomas Hamelryck at the University of Copenhagen.

My current work develops and applies Stein-based methods to underwater robotic localization and mapping.