RISIS Online School on Tools and methods for analysing complex Science, Technology and Innovation (STI) systems

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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.