This project is funded by the European Union under Horizon2020 Research and Innovation Programme Grant Agreement n°824091
European Union
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RISIS Online School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems

Feb 15 @ 2:30 pm - Feb 26 @ 12:00 pm

The Online Winter School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems: A gentle introduction to Network Science (NS),
Spatial Models (SM) and Machine Learning (ML) is organized by Research Institute of  Sustainable Economic Growth (CNR-IRCrES) in collaboration with Austrian Institute of Technology (AIT) and will take place on online platform from 15th to 26th of February 2021.

Deadline for request of participation: 18th of November 2020

Course main objectives:

The training will provide participants with the essential tools for a correct application of some popular NS, SM and ML methods in various STI contexts. In particular:

ML techniques proves useful for factor importance detection, as well as for classification purposes in a model-free stance;

NS and SM techniques are useful to identify and study structure and dynamics of large and complex STI communities;

The course foresees three modules (one on ML, one on NS, and one on SM) with the aim of balancing theory and applications. Participants will run some exercises assigned by the instructor under his supervision.

Target audience: 

Target audience for this course are researchers in research policy, higher education, and innovation studies with a quantitative orientation, who aim to extend their competence on ML, NS, and SA analysis.

Senior scientists, early career researchers and PhD students at the last phase of their training;

Officers from the policy making level;

Research associations.

Course prerequisites:

Knowledge on basic principles of statistics

Interest in STI studies


Call for application and programme

Form for submission

Contact person: Dr Marco De Biase (CNR-IRCrES)


Feb 15 @ 2:30 pm
Feb 26 @ 12:00 pm
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Antonio Zinilli (CNR-IRCrES)