Research

Much of my research lies at the intersection of methodological statistics, machine learning, and applied statistics. Data-related problems sparking my curiosity are constant sources of fresh ideas for my research. I am particularly passionate about scientific problems and working in collaborative and interdisciplinary projects where data-driven research demands the development of novel data analysis methods. I am always open to explore new fields and initiate new collaborations.

More specifically, my research interests center on latent variable models in application to high-dimensional and complex data. Within this area, my work primarily focuses on model-based clustering and classification, statistical network analysis, variable selection, and dimension reduction.

Some of my current projects involve Bayesian optimization, clustering objects, database matching, and analysis of computer experiments.


Current PhD students

  • Sara Geremia – visiting from Univ. of Trieste, co-supervision with Prof. Domenico de Stefano
    Community detection methods for EU-funded research collaboration networks.

  • Brian Hassett – co-supervision with Prof. Riccardo Rastelli
    Latent position models for time-dependent multidimensional network data.

  • CJ Clarke
    Latent variable models for collections of networks.

  • Niyati Seth
    Bayesian combinatorial optimization techniques with application to facility location problems.

  • Iuliia Promskaia – co-supervision with Prof. Adrian O’Hagan
    Model-based clustering methods for networks with edge weights and node features.

  • Ganesh Babu – co-supervision with Prof. Claire Gormley
    Model-based clustering and classification methods for high-dimensional data with spatial and temporal dependence.


Former PhD students

  • Matt Nagle – co-supervision with Prof. Aisling Ní Annaidh
    Improving reconstructive surgery: Machine learning approaches for biomechanical skin assessment (2025).

  • Thais Pacheco – co-supervision with Prof. Brendan Murphy
    Record linkage approaches for matching databases with nested records (2025).

  • Noemi Corsini – visiting from University of Padova, co-supervision with Prof. Giovanna Menardi
    Advances in density-based clustering for complex data (2025).

  • Xian-Yao Gwee – co-supervision with Prof. Claire Gormley
    Bayesian nonparametric models for network data (2024).