PhD Programme in Computer Science and Mathematics

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Decreto Ministeriale n. 118 del 2 marzo 2023, a valere sul PNRR, Missione 4, componente 2 “Dalla Ricerca all'Impresa” - - Investimento 4.1 “Estensione del numero di dottorati di ricerca e dottorati innovativi per la pubblica amministrazione e il patrimonio culturale”.

Maria Lucia Bernardi

Code: DOT1302947

CUP: H91I23000500007

Tech4Math-Math4STEM

The research project intends to contribute to promoting 21st-century citizens’ learning of mathematics and STEM disciplines, through the identification of a set of guidelines regarding teachers’ professional development that could foster the integration of technology into teaching practices. To reach this aim, different teachers’ knowledge models will be reviewed and compared. Informed by the findings of this preliminary analysis, some teachers’ professional development activities will be designed and experimented with in two different countries, Italy and Portugal. Mixed methods, both qualitative and quantitative, will be used to analyse the results of this comparative study. The discussion will offer theoretical considerations and practical suggestions. The research will have a direct impact on our territory through teaching experiments on STEM subjects that will involve schools in the area and will pay particular attention to promoting the development of scientific competencies in female students.


Alessandro Cannone

Code:

CUP: H91I23000500007

Non-Local Differential Problems in Quantum Science

My research project involves the study of nonlinear equations with non-local interactions (Pekar-Choquard equations, Hartree-type equations, dispersive nonlinear equations and systems of equations, fractional Schrodinger equations). These problems find applications in Mechanics Quantum, in dislocation problems, in phase transition, in image reconstruction. In particular, one of the objectives will be to address the study of some classes of interaction functionals, where the classical PDE theory fails due to presence of non-locality, such as Thomas–Fermi–Dirac–von Weizsäcker (TFDW) type density functionals deriving from the description of the response of a graphene.


Nicola Fanelli

Code: 39-413-02-DOT1302947-6150

CUP: H91I23000690007

Analysis and valorization of digitized artistic heritage using Artificial Intelligence techniques

Research topics will cover the development of Artificial Intelligence models for the analysis and enhancement of digitized artistic heritage. The project has an impact on the territory, as artistic heritage plays a role of strategic importance for the country's economic and cultural growth. In fact, the expected results, to the extent of wider enjoyment of artistic heritage, would have positive repercussions on the cultural sector, which has been severely affected by the recent pandemic crisis. In addition, the research responds to the emerging demand for new professional figures whose skills lie at the intersection of the humanities and computer

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