I was researcher in Theoretical Computer Science (80--95). I was interested in Tree Automata (see the TATA book) and their applications (a paper on Set Constraints). Then I moved to Machine Learning (95--). I studied Teaching Models using Kolmogorov Complexity; Learning from Positive Examples; Conditional Random Fields for Trees; Grammatical Inference Learning Algorithms for Trees and Boosting Algorithms for Multi-Task Learning. More recently I studied graph-based learning (see Hypernode Graphs and their application to the skill rating problem for multiple player games).
Last I moved to Natural Language Processing. We studied the combination of Language Models and Knowledge based models along the Impress project and we developed Mangoes, a Python toolbox for constructing and evaluating Language Models. More recently, we developed collaborations with cognitive scientists on the comparison on how humans and machines learn language.
See Google Scholar publications or DBLP publications