Dottorando in Energetica , 39o ciclo (2023-2026)
Dipartimento Energia (DENERG)
Profilo
Dottorato di ricerca
Argomento di ricerca
Use of Artificial Intelligence Techniques for the Optimization of Innovative Solar Cells Production
Tutori
- Eliodoro Chiavazzo
- Pietro Asinari
- Aldo Di Carlo
Interessi di ricerca
Biografia
As a student I mainly focused on the many aspects of energy production (both fossil and renewable), transmission, storage, use, and policies, while also developing a broader knowledge of the engineering disciplines, studying subjects related to mechanics, fluid dynamics, electronics, and artificial intelligence. Throughout my academic career I had the chance to develop many projects (both alone and in a group) and to do research work both during an internship at the Energy Center Lab of the Politencico di Torino (2021) - focusing on the characterization of the equivalent Thévenin circuits for Lithium-ion batteries - and during my stay at University of Illinois Chicago (2022-2023) - focusing on the application of machine learning techniques to model the sorption capacity of an innovative atmospheric water harvesting device.
Now, as a Ph.D. student, I am working on the optimization of innovative Perovskite-based solar cells through Artificial Intelligence techniques in collaboration with the Italian National Research Council (CNR) and the CHOSE (Polo Solare Organico della Regione Lazio).
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- Barletta, Giulio; Trezza, Giovanni; Chiavazzo, Eliodoro (2024)
Learning Effective Good Variables from Physical Data. In: MACHINE LEARNING AND KNOWLEDGE EXTRACTION, vol. 6, pp. 1597-1618. ISSN 2504-4990
Contributo su Rivista - Barletta, Giulio; DI PRIMA, Piera; Papurello, Davide (2022)
Thévenin's Battery Model Parameter Estimation Based on Simulink. In: ENERGIES, vol. 15. ISSN 1996-1073
Contributo su Rivista