My research lies at the intersection of Information Theory, Probability Theory and Functional Analysis. To get to know my views on the (fundamental) connection among the fields you can check out my thesis. Applications of my results range from Learning Theory (see here, here, here, here, and here), to Probability Theory (see here, here) and Estimation Theory (see here and here).

The work I am most proud of is, at the moment, only available as a conference paper (a longer version is on its way). It encapsulates my views in which Information Measures simply are a bridge between spaces of measures and spaces of functions and therein lies their power.

My current interests consist in a deeper exploration of the framework I set up during my PhD, and I am grateful for being able to do so with Marco Mondelli.


Journals & Conferences