Rocco Giudice

Dottorando in Energetica , 38^o ciclo (2022-2025)
Dipartimento Energia (DENERG)

rocco.giudice@polito.it

Profilo

Dottorato di ricerca

Argomento di ricerca

Scalable and Interoperable AI-based Energy Management and Information Systems in buildings

Tutori

Presentazione della ricerca

Poster

Interessi di ricerca

Innovative Energy Systems

Energy efficiency in buildings and in industry

Innovative HVAC systems

Smart buildings and urban energy modelling

Biografia

Rocco Giudice gratuated with honours in Energy and Nuclear Engineering at Politecnico di Torino in October 2022.
From November 2022 he is a Ph.D. student at BAEDA Lab, where he is focusing on applications of Artificial Intelligence in the field of Energy Management and Information Systems (EMIS), for enhancing energy management in buildings. In particular, he is investigating how to make Decision Support Systems (DSS) in buildings more scalable and interoperable. Main topics investigated are: Anomaly Detection and Diagnosis (ADD), advanced energy benchmarking, Fault Detection and Diagnosis (FDD), semantic metadata models and Large Language Models for buildings.

Pubblicazioni

Coautori PoliTO

Pubblicazioni degli ultimi anni

Pubblicazioni per tipo

Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris

Perini, Marco; Antonucci, Daniele; Giudice, Rocco; Piscitelli, Marco Savino; Capozzoli, ... (2025)
BrickLLM: A Python library for generating Brick-compliant RDF graphs using LLMs. In: SOFTWAREX, vol. 30. ISSN 2352-7110
Contributo su Rivista
Giudice, Rocco; Piscitelli, Marco Savino; Chiosa, Roberto; Capozzoli, Alfonso (2024)
A Data-Driven Process for Optimal Incentive Sharing in Collective Self-Consumption Groups of Residential Users. In: 9th International Building Physics Conference, IBPC 2024, Toronto, Canada, 25 - 27 July, 2024, pp. 19-24. ISSN 2366-2557. ISBN: 9789819783083
Contributo in Atti di Convegno (Proceeding)
Piscitelli, Marco Savino; Giudice, Rocco; Capozzoli, Alfonso (2024)
A holistic time series-based energy benchmarking framework for applications in large stocks of buildings. In: APPLIED ENERGY, vol. 357. ISSN 0306-2619
Contributo su Rivista
Morra, Lia; Azzari, Alberto; Bergamasco, Letizia; Braga, Marco; Capogrosso, Luigi; ... (2023)
Designing Logic Tensor Networks for Visual Sudoku puzzle classification. In: 17th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy 2023), Certosa di Pontignano, Siena (Italia), July 3-5, 2023, pp. 223-232. ISSN 1613-0073
Contributo in Atti di Convegno (Proceeding)