I’m a fourth year PhD candidate in Statistics at Duke University, North Carolina. Previously, I obtained a Bachelor degree in “Economics and Finance” at Università degli studi di Bologna (the oldest in the world!). I continued my studies in Turin where I received a master’s degree in “Stochastics and Data Science” at the University of Turin and in parallel a master in “Statistics and Applied Mathematics” at Collegio Carlo Alberto. In the meanwhile, I did an exchange period at the University of Lund, Sweden.
In my free time, I really enjoy climbing. This is a map created with the R package leaflet of the places and routes that I climbed! The code can be found in this Github repo. Here’s my Mountain Project profile.
Interests and Research
My research interests include Bayesian Modeling, Bayesian Nonparametric, Bayesian Factor regression, Hierarchical Models, Scalable Algorithms for Bayesian Models, Spatial Statistics, Conformal Inference. This is my Google Scholar profile!
I am currently develping models for environmental epidemiology applications with my PhD supervisor David B. Dunson. In particular, we are interested in modelling complex-dose response curves for chemical exposures. Several statistical challenges include highly correlated covariates and large p small n datasets.
For my master thesis I worked on a nonparametric Multi-Armed Bandits for Species Discovery with my Master supervisor Stefano Favaro and Federico Camerlenghi. We applied Multi-armed bandits to iterative experimental design in multi-tissue single-cell RNA-seq data together with Bianca Dumitrascu and Barbara Engelhardt.
Pubblications and Preprints
- Ferrari, F. * , Dunson, D. B. Bayesian Factor Analysis for Inference on Interactions. Journal of the American Statistical Association just-accepted (2020): 1-29. link.
- Ferrari, F. * , Dunson, D. B. Identifying main effects and interactions among exposures using Gaussian processes. Annals of Applied Statistics just-accepted (2020). ArXiv. Supplementary Materials.
- Camerlenghi, F.* , Dumitrascu, B.*, Ferrari, F. * , Engelhardt, B. E., Favaro, S. Nonparametric Bayesian Multi-Armed Bandits for Single Cell Experiment Design. Annals of Applied Statistics just-accepted (2020). ArXiv.
- Poworoznek, E.*, Ferrari, F., Dunson, D. B. Bayesian semi-parametric factor modelling with the infinite package for R. CRAN
- Jiang M. *, Ferrari, F., and Dunson D. B. Structural Equation Models for Environmental Health Outcomes.
- Ferrari, F. *, Engel S, Dunson D and Herring A. Bayesian Factor Copula for Inference on Dose-Response Curves
- Ferrari, F. *, Wong, U. P-nDCG: a new learning-to-rank metric for large lists of imbalanced binary data.
- STA723: Case Studies (Spring 2020)
- STA523L: Statistical Programming (Fall 2019 and Fall 2020)
- STA101: Data Analysis and Statistical Inference (Summer 2019)