Education

PhD in Statistics, Bocconi University, 2021

Research Interests

Bayesian Data Analysis, Computational Statistics, Epidemiology

Affiliation

Tenure-track Assistant Professor of Statistics, University of Torino

Selected Works

  • Anceschi, N., Fasano, A., Durante, D., and Zanella, G. (2023). Bayesian conjugacy in probit, tobit, multinomial probit and extensions: a review and new results. Journal of the American Statistical Association, 118(542), 1451-1469.
  • Fasano, A., Durante, D., and Zanella, G. (2022). Scalable and accurate variational Bayes for high-dimensional binary regression models. Biometrika, 109(4), 901-919.
  • Fasano, A., and Durante, D. (2022). A class of conjugate priors for multinomial probit models which includes the multivariate normal one. Journal of Machine Learning Research, 23(30), 1-16.