My research intersts lie in the broad area of statistical machine learning with broader goal to build methods that combine the strengths of statistics and computation aspiring to answer scientific questions with impact in real life.

My phd focus was on Bayesian non parametric modelling for random graphs, complex networks, time interaction data and on practical Bayesian non parametric methods and theory for a variety of applications.

My research to date includes more broadly Bayesian methods, deep generative models, unsupervised learning techniques, point processes and stochastic processes with applications in social science, epidemiology and finance.