The 16th Advanced Summer School in Economics and Econometrics will be held from August 7th to August 13th, 2022, at the University Campus in Rethymno, Crete. The topic of the School is “Bayesian Networks in Policy and Society“.
Dr. Marco Scutari, Senior Researcher in Bayesian Networks and Graphical Models, Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Polo Universitario Lugano, Switzerland, will be the guest lecturer.
Up to 30 students will be accepted to the program.
Since 2006 the Department of Economics of the University of Crete is successfully running its Advanced Summer School in Economics and Econometrics. The broader objective of this series of events is to provide advanced training for young researchers from all over Europe and beyond on important disciplines of economics and econometrics. The Summer School follow a traditional structure: lectures in the morning and computer practical sessions in the afternoon. The specialized topic varies from year to year and reflects issues that are currently lively areas of new research and policy interest. The faculty is comprised of leaders in the field, and offers an overall coverage of the specialist area.
Magdalena Erdem, ASSEE 2014
The course justified my expectations completely!
The organization of the course was excellent and I do not hesitate to recommend ASSEE to anyone who wants to learn some theory of interest as well as practical aspects of econometrics.READ MORE TESTIMONIALS
Through systematic interaction participants will be encouraged to compare their approaches and examine their research work. A unique opportunity will be given to advanced doctoral students to present their own work and to discuss it with the Distinguished Guest Professor. The Advanced Summer School Series on Economics and Econometrics facilitates the establishment of contacts between young researchers coming from various universities and research institutions throughout Europe.
Dr. Marco Scutari is a Senior Researcher in Bayesian Networks and Graphical Models at the Dalle Molle Institute of for Artificial Intelligence (IDSIA), Polo Universitario Lugano, Switzerland. He has authored/coauthored more than 25 scientific articles on Bayesian networks and their applications, as well as two books on the subject, “Bayesian Networks with Examples in R” and “Bayesian Networks in R with Applications in Systems Biology“. He is the author and maintainer of the bnlearn R package, which implements key algorithms covering all stages of Bayesian network modelling: data preprocessing, structure learning combining data and expert/prior knowledge, parameter learning, and inference.