I am a Rita Levi-Montalcini Research Fellow working at the University of Brescia, Italy. This fellowship (also known as "Rientro dei Cervelli") by the Italian Ministry of Research and Education enables young researchers to apply for a three years research fellowship in an Italian university of their choice (success rate of less that 8%).
My research is about learning and reasoning with uncertain and sparse data. I co-authored of more than 50 peer-reviewed papers, including several journal papers, and co-edited two books.
Prior to my personal fellowship, I was Academic Director of the Cardiff University Data Science Academy, and Senior Lecturer at the School of Computer Science and Informatics of Cardiff University.
Conventional Bayesian approaches for fusion require accurate models of priors and likelihoods. However, in many situations – such as emergency management – we have little training data. Rather, the uncertainty in most information is normally subjectively assigned by experienced indviduals. This project will explore from first principles ways to combine such uncertain information together.
Knowledge compilation is a key direction of research for dealing with the computational intractability of general propositional reasoning. A propositional theory is compiled off-line into a target language, which is then used on-line to answer a large number of queries in polynomial time. This project will derive Python implementations of existing algorithms, comparing them with existing closed-source implementation from an efficient perspective.
via Branze, 38, Brescia
+39 030 3715 453