I obtained both my Master’s and PhD in Statistics from the University of Geneva. My research focuses on the statistical analysis of networks and graphs, with particular emphasis on three core areas: computational methods, theoretical foundations, and practical applications, notably in genomics and neuroscience. More recently, I have developed a growing interest in differential privacy and nonparametric statistics, particularly as they apply to network and graph-based data.
I have served as a teaching assistant for numerous undergraduate courses in mathematics, probability, and statistics. In addition, I have supported more advanced graduate-level courses, including Advanced Topics in Survey Methods, Model Selection in High Dimensions, and Forecasting with Applications in Business.
- University of Geneva, 2024
Education & Training
- SC22 Best Paper (2022)
Miglioli, C. and Canini, M. and Vignotto, E. and Pecco, N. and Pozzoni, M. and Victoria-Feser, M.P. and Guerrier, S. and Candiani, M. and Falini, A. and Baldoli, C. and Cavoretto, P.I. and Della Rosa, P.A. (2024). The Maternal-Fetal Neurodevelopmental Groundings of Preterm Birth Risk. Heliyon 10(7):e28825
Besta, M. and Miglioli, C. and Labini, P.S. and Tetek, J. and Iff, P. and Kanakagiri, R. and Ashkboos, S. and Janda, K. and Podstawski, M. and Kwasniewski, G. and Gleinig, N. and Vella, F. and Mutlu, O. and Hoefler, T. (2022). ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations} IEEE Press, Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, Dallas, TX, US, pp. 600-616. Winner of the Best Paper SC award 2022.
Besta, M. and Grob, R. and Miglioli, C. and Bernold, N. and Kwasniewski, G. and Gjini, G. and Kanakagiri, R. and Ashkboos, S. and Gianinazzi, L. and Dryden, N. and Hoefler, T. (2022). Motif Prediction with Graph Neural Networks. ACM, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington DC, USA, pp. 35–45.
Miglioli, C. and Bakalli, G. and Orso, S. and Karemera, M. and Molinari, R. and Guerrier, S. and Mili, N. (2022). Evidence of antagonistic predictive effects of miRNAs in breast cancer cohorts through data-driven networks. Scientific Reports 12, 5166.
- Computational and Nonparametric Statistics
- Differential Privacy
- Graphical Models and Random Graphs
- Applications to Life Sciences
