Contacts
The Bocconi research unit on Bayesian statistics will host an online seminar series in which outstanding young researchers will have the opportunity to present their work and get feedback from toplevel senior scholars

The COVID-19 emergency has put a halt to scientific conferences and scholars' international mobility. This particularly affected young researchers, who need to showcase their work and build an international network. However, the recent lockdown has also boosted online meetings and interactions, giving a taste of new formats for working and teaching. In this spirit, the Bayesian Learning Lab (BayesLab), a newly established unit of the Bocconi Institute for Data Science and Analytics (BIDSA), has decided to turn the current travel limitations into an opportunity to offer visibility to outstanding junior Bayesians through a webinar series, Junior Bayes Beyond the Borders (JB3). The series is jointly organized with j-ISBA, the junior section of the International Society for Bayesian Analysis (ISBA).

Bayesian statistics is named after the celebrated Bayes' Theorem, published in 1763. It is a principled approach to inference that combines prior information with data, leading to effective 'posterior' estimates, predictions and uncertainty quantification. Thanks to the advent of powerful computers and new algorithms, the popularity of Bayesian methods has been soaring in the 21st century.

«Bayesian statistics has a long tradition at Bocconi» says Igor Prünster, Professor of Statistics at Bocconi University and BIDSA director. «This legacy was initiated by professors Regazzini and Cifarelli in the 1970s and has been steadily growing over 50 years, with the current Bayesian Faculty holding leading positions in top journals and international organizations. Maybe even more importantly, Bocconi is continuing to nurture new generations of Bayesian statisticians. Both our MSc and PhD students are highly appreciated worldwide and many have found immediate placement in top universities like Stanford, UC Berkeley and Duke, just to name a few. Scouting and fostering young talents will be a key goal of the BayesLab».

This inter-generational spirit is reflected in the upcoming webinar series, where the invited junior speakers will have the chance to engage in discussion from a top senior scholar. Since the importance of this initiative goes beyond the current emergency, the webinars will continue as an annual series.

The first edition of Junior Bayes Beyond the Borders will start on 25 June 2020 and run until mid-July, featuring talks by the five finalists of the 2020 "L.J. Savage Award", the highly prestigious prize that ISBA and the American Statistical Association bestow annually on the best doctoral dissertations in Bayesian statistics. The links to each webinar will be shared on the series website.


Find out more

D. Spiegelhalter and K. Rice (2009). Bayesian Statistics. Scholarpedia 4, 5230.

K. Cowles, R. Kass and T. O'Hagan. What is Bayesian Analysis?

B. de Finetti (1974). Bayesianism: Its Unifying Role for Both the Foundations and Applications of Statistics. International Statistical Review 42, 117-130.

Research