Academic interests
I am interested in scalable likelihood-free inference. In particular, my research focuses on improving sampling efficiency using methods like sequential Monte Carlo, active learning and surrogate models.
Background
I have a Bachelor's degree in mathematics and a Master's degree in computational science with applications in physics. The focus of my Master's thesis was on causal discovery in networks where there is hidden confounding, with applications in neuroscience.