Giorgio Corani

About me


PhD in Information Engineering (Politecnico di Milano)


Senior researcher at IDSIA, member of the Imprecise Probability Group.



Research interests



Bayesian Machine Learning


Probabilistic Graphical Models


Applied Statistics and Data Mining



Publications


My list of Publications


My Google Scholar page.


Best Paper Prize at the International Environmental Modelling and Software Conference 2002 (Lugano, Switzerland).



Conferences organization: PGM 2016 & ISIPTA 2017



I have co-organized, co-chaired and co-edited the proceedings of two conferences, held in Lugano in respectively 2016 and 2017:


  • PGM 2016 (The Eighth International Conference on Probabilistic Graphical Models)

  • ISIPTA 2017 (The Tenth International Symposium on Imprecise Probability: Theories and Applications)



Program committees



AAAI (2018 ,2019): AAAI Conference on Artificial Intelligence


IJCAI (2015, 2016, 2018): Int. Joint Conference on Artificial Intelligence


UAI (2016, 2018): Conference on Uncertainty in Artificial Intelligence


NIPS (2018): Conference on Neural Information Processing Systems


ECAI (2014, 2016, 2018): European Conference on Artificial Intelligence


PGM (2014, 2016, 2018): European Workshop on Probabilistic Graphical Models


ISIPTA (2009, 2011, 2013, 2015, 2017, 2019): International Symposium on Imprecise Probability: Theories and Applications:


DMIN (2011 , 2012 , 2013 , 2014 ): International Conference on Data Mining



Reviewing



Reviewer for many different journals such as Machine Learning, Artificial Intelligence, Artificial Intelligence in Medicine, etc.


Outstanding reviewer certificate from the journal Environmental Modelling and Software.


Certificate of reviewing from the Int. Journal of Approximate Reasoning.



Teaching



Applied Statistics

Bachelor of Business Engineering.


Analysis of Sequential Data

Master of Science in Information Engineering (co -teacher).


Uncertain Reasoning and Data Mining

Master of Science in Information Engineering (co -teacher).



Code



Bayesian hypothesis testing in machine learning

Slides and code of our tutorial at ECML/PKDD 2016:

G. Corani, A. Benavoli, J. Demsar


Naive Credal Classifier

The open source implementation of the naive credal classifier is the JNCC2.


Credal Model Averaging

The R implementation of credal model averaging for logistic regression is due to A. Mignatti. The algorithms are discussed in these two papers (link1, link2). The software and the marmot data set used in those papers is available here.