My research interests regard statistics from both a theoretical and an applied point of view. 

Current research involves the extension to more flexible tail dependence regimes of the recent X-vines models for multivariate extremes. The current framework is only adapt for asymptotic dependence, and it would be extremely ;) interesting to find ways to bring its flexibility to an even higher degree by incorporating asymptotic independence.

During my PhD, I have explored the conceptualization and construction of copula-like models for bivariate discrete random vectors in an attempt to bridge the gap between the well known application of copulas in the continuous case and the less investigated - for various reasonable motivations - case of discrete margins. In my first postdoc of one year, I have finalised natural extensions to the multivariate and non-rectangular cases. Furthermore, I have also sought a deeper understanding of the  probabilistic tool  underlying this approach, the  I-projections and the more general phi-projections, which lead to work related to the minimum information copula principle. 

In the realm of applications, I have been mainly interested in the hydrological ones. After my PhD project involving the statistical analysis and modeling of the daily rainfall interarrival times and rainfall depths, I am currently focused on investigating the dependence between the rainfall depths and the length of the corresponding cluster of rainy days.

During my PhD and master thesis, I have also worked in the development of a method for approximating the first passage time probability density and/or distribution function of some one dimensional diffusions, which is based on truncating a series expansion involving the generalised Laguerre polynomials and the gamma probability density.