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Associate Professor
Department of Decision Sciences

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Courses a.y. 2020/2021


Courses previous a.y.

Biographical note

Simone Padoan is an associate professor at the Bocconi University of Milan from 2020. He is research fellow at the Euro-Mediterranean Center on Climate Change (CMCC) from 2020. From 2016 he is a research fellow at the Bocconi Institute of Data Science and Analytics (BIDSA), Bocconi University of Milan, Italy.

Academic CV

he received his PhD in Statistical Science in 2008 and the Master Degree in Statistics in 2004 from the University of Padua.

During his PhD he spent about two years at the school of mathematics and statistics at the University of New South Wales

He has carried out research as: a post-doc at Ecole Poytechnique Fédérale de Lausanne from February 2008 to December 2010, a research fellow at the University of Bergamo from January 2011 to September 2011 and a senior research fellow at the University of Padua from October 2011 to August 2012.

Research areas

Extreme value theory, applied probability, nonparametric statistics, spatial statistics, time series, computational statistics, estimation methods for complex models based on Bayesian and likelihood approaches.


Editorial Activity

Associate Editor: Stochastic Models (2019 - ); Extremes (2019 - );


  1. Falk, M., Padoan, S. A. and Wisheckel, F. (2019). Generalized Pareto Copulas: a Key to Multivariate Extremes. Journal of Multivariate Analysis, 174, 104538.
  2. Falk, M., Padoan, S. A. and Wisheckel, F. (2019). Conditional Tail Independence in Archimedean Copula Models. Journal of Applied Probability, 56(3), 858-869.
  3. Guillou, A., Padoan, S. Aand Rizzelli, S. (2018). Inference for Asymptotically Independent Sample of Extremes. Journal of Multivariate Analysis, 167, 114-135.
  4. Falk, M., Khorrami, A. and Padoan, S. A. (2018). On Multivariate Records from Random Vectors with Independent Components. Journal of Applied Probability, 55, 1-11.
  5. Beranger B., Padoan, S. A. and Sisson S. A. (2017). Models for extremal dependence derived from skew-symmetric families. Scandinavian Journal of Statistics, 44(1), 21-45.
  6. Marcon G., Padoan, S. A. and Antoniano-Villalobos, I. (2016). Bayesian Inference for the Extremal Dependence. Electronic Journal of Statistics, 10(2), 3310-3337.
  7. Genton, M. G., Padoan, S. A. and Sang, H. (2015). Multivariate max-stable spatial processes. Biometrika, 102(1), 215–230.
  8. Padoan, S. A. (2013). Extreme Dependence Models Based on Event Magnitude. Journal of Multivariate Analysis, 122, 1-19.
  9. Davison, A. C., Padoan, S. A. and Ribatet, M. (2012). Statistical Modelling of Spatial Extremes, with discussion. Statistical Science, 27(2), 161–186.
  10. Wand, M. P., Ormerod, J. T., Padoan, S. A. and Fruhrwirth, R. (2011). Mean Field Variational Bayes for Elaborate Distributions. Bayesian Analysis, 6(4), 847–900.
  11. Padoan, S. A. (2011). Multivariate Extreme Models Based on Underlying Skew-t and Skew-Normal Distributions. Journal of Multivariate Analysis, 102, 977–991.
  12. Padoan, S. A., Ribatet, M. and Sisson, S. A. (2010). Likelihood-Based Inference for Max-Stable Processes. Journal of the American Statistical Association, Theory & Methods.