This project is funded by the European Union under Horizon2020 Research and Innovation Programme Grant Agreement n°824091
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Methods in Action: Pitfalls and Potentialities of Probabilistic Graphical Models

May 8 @ 9:00 am - May 15 @ 12:00 pm

The “Methods in Action Series” course “Pitfalls and Potentialities of Probabilistic Graphical Models” is organized by Department of Computer, Control and Management Engineering Antonio Ruberti, Sapienza University of Rome, and will take place on online platform on  8, 11  and 15 May 2023.





Topic and objective

• Introduce Graphical Models to identify causal relationships
• Introduce to the use of Graphical Models for explanation or for predicting the effects of policy interventions.
• Offer a review of the methods for causal discovery based on graphical models that were developed in the past three decades.
• Present illustrations and applications to real data
• Practice in groups on the presented models
Online course including:
• On-line lectures presenting the main methods for causal discovery based on graphical models
• Group exercises where participants will experiment the different approaches available based on graphical models
• Plenary discussion on the exercises carried out


Course programme

8 May 2023

9:00–09:15 Introduction to the Course

09:15–10:30 Lecture on Graphical Models for Causal Inference by Alessio Moneta

10:30-10:45 Coffee break

10:45–11:30 Examples and illustrations in R by Alessio Moneta

11:30–12:00 Task assignment


11 May 2023

13:00–15:00 interim discussion with groups lead by Simone Di Leo and GiammarcoQuaglia


15 May 2023

9:00–11:00 Group presentations

11:00–12:00 Final discussion and assessment



Alessio Moneta is Associate Professor of Economics at the Institute of Economics and coordinator of the PhD Program in Economics, Scuola Superiore Sant’Anna, Pisa. His research interests lie on causal inference in macroeconometrics, model validation, applied macroeconomics, and methodology of economics.


Organising Committee:

Alessandro Avenali, Cinzia Daraio, Giorgio Matteucci.


Technical Support: 

Simone Di Leo, Giammarco Quaglia.


Target audience:

The course aims at involving participants among the following categories:

• Early career researchers
• PhD students
• People from the policy making world wishing to extend their analytical capabilities
• Data scientists interested in knowing the potentialities Graphical Models for causal inference


Course prerequisites:

Basic requisites for admission will be:

•Knowledge of basic principle of statistics
•Basic knowledge of the software R

Cost and Fees:

No registration fees to be paid by European participants.

Registration: by email to the organizer including a CV and a short statement of interest.


Deadline for request of participation:

April 30th, 2023

Contact person:

Simone Di Leo, 


May 8 @ 9:00 am
May 15 @ 12:00 pm
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DIAG – Sapienza University Rome