I am an Academy of Finland postdoctoral research at Aalto University working on probabilistic machine learning. My research focuses on the intersection of flexible Bayesian modelling families (e.g., Gaussian processes, Bayesian neural networks, Polya trees, ...) and probabilistic circuits aka deep tractable models. I am particularly interested in modelling families that are flexible (nonparametric), but allow certain qunatities (e.g., marginal, posterior) to be computed tractably or ways to obtain tractable surrogates that are approximatly equal to the model of interest.
For details, see my website and my Google scholar profile.
In addition to my research, I am part of the open-source project Turing.jl and a keen supporter of dynamic and probabilistic programming.