Academic interests
Luca's academic activity is centered around statistics and machine learning for graph structured data and graph populations. He is currently interested in statistical relational learning and possible applications to chemistry and neuroscience. More recently, his work has been focusing on the study of the aforementioned problems from a geometric point of view. Previous positions focused on probabilistic graphical models for continuous and count data in high-dimensional scenarios.
Background
Luca acquired his master's degree in mathematics at the University of Trento, with a thesis on penalized likelihood inference methods for Gaussian covariance graph models (2023). In 2024 Luca worked as an early-stage researcher at the University of Padua, where he investigated the topic of probabilistic graphical models for count data.
PhD project
“ Structure-generating models for transition metal complexes ”.
The initial aim of the project is to study and develop statistical learning techniques for the assessment of the plausibility of a given transition metal complex within a context defined by both observational data and theoretical knowledge. Future developments will focus instead on leveraging these methodologies in order to generate new complexes on the basis of desired properties and features.
Supervisors:
- Basil Ell , Bielefeld University, Faculty of Technology
- Johan Pensar , University of Oslo, Department of Mathematics
- Riccardo De Bin , University of Oslo, Department of Mathematics