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Her program: open the International Society for Bayesian Analysis to contiguous scientific communities without losing the bayesian identity

Sonia Petrone (Department of Decision Sciences) has been elected president 2014 of the International Society for Bayesian Analsyis (ISBA).

ISBA is the most important scientific society for bayesian statistics and promotes the development and application of bayesian analysis for the solution of theoretical and applied problems in science, industry and government. Candidates for president are nominated by a highly qualified Nomination Committee and then chosen through a world-wide election by ISBA members. Petrone will be in charge for three years, as president-elect for 2013, as ISBA president 2014, and as past-president in 2015.

Together with the impressive growth of bayesian methods and applications, ISBA has been developing in a wide and extremely active community. Bayesian methods are nowadays used in a wide range of applications, from economics to bioinformatics, environmental and climate studies, public health policies, life and social sciences. Key strengths of the amazing success of Bayesian Statistics are its sound theoretical foundations and the enormous progresses in computational power that allow to apply Bayesian methods to highly complex problems and big data.

Facing this rapid development is a main challenge that Petrone addresses in her presidential program for ISBA. "Bayesian statistics, but more generally statistical sciences, are facing extremely fast and challenging transformations", she says. "The boundary between statistics and areas such as information theory and machine learning has become quite subtle. Think of the statistical analysis of world-web data! I want to work to foster the interaction of ISBA with contiguous research areas and scientific communities, such as computer sciences, and with fields where subjective probability is the natural way of thinking, such as economics. In brief I would work for opening ISBA more and more to the 'external world', but keeping the unifying methodology given by the bayesian approach".

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