My research is motivated by the understanding of the structure(s) which govern(s) the behaviour of complex systems. Mostly, I have been working with high-throughput data generated by biological organims, regarded as layers of components of different natures which interact with each other possibly fulfilling different goals.
To this end, I am interested in probabilistic graphical modelling as a convenient way of representing the system under study and how its constituting elements interact. I am often faced with high-dimensional data posing both statistical and computational challenges. Missingness in the data sets at hand can also be a hindrance. Data sets are heterogeneous (e.g. mixing discrete and continuous data), sampling is certainly not independent and identically distributed and off-equilibrium and measurements noisy.
Recently, I am moving towards a causal interpretation of learnt relationships, hopefully revealing realistic mechanisms which explain the inner functioning of the system.
I have also been involved in the study of epidemiological models at different scales.
