• Collegio di Architettura e Design. Componente
• Collegio di Ingegneria Elettrica ed Energetica. Componente invitato

Bachelor of Science

• Energetica dell'edificio. A.A. 2017/18, INGEGNERIA ENERGETICA. Collaboratore del corso
• Energetica dell'edificio. A.A. 2017/18, INGEGNERIA ENERGETICA. Collaboratore del corso
• Energetica dell'edificio. A.A. 2018/19, INGEGNERIA ENERGETICA. Collaboratore del corso
• Energetica dell'edificio. A.A. 2018/19, INGEGNERIA ENERGETICA. Collaboratore del corso
• Fisica dell'edificio e climatizzazione. A.A. 2019/20, INGEGNERIA ENERGETICA. Collaboratore del corso
• Fisica dell'edificio e climatizzazione. A.A. 2019/20, INGEGNERIA ENERGETICA. Collaboratore del corso

Projects funded by commercial contracts

• Contratto di Ricerca commerciale avente ad oggetto “Data-Driven Performance Analysis for Industrial Energy Systems: Standardizing Analytics Processes through generative AI” , (2024-2025) - Responsabile Scientifico
  Commercial Research
• Advanced data-driven smart reporting systems to enhance energy management in industrial and office buildings , (2023-2024) - Responsabile Scientifico
  Commercial Research

• Simone Amico. Programme in Energetica (cycle 40, 2025-in progress)
• Federica Gallina. Programme in Design E Tecnologia. Persone, Ambiente, Sistemi (cycle 40, 2024-in progress)
  Research subject: Development of strategies and technologies for net-zero carbon buildings, applying LCA methods for operational and embodied carbon accounting. Benchmark analysis and thresholds based on case studies
  
  SUSTAINABLE AND CIRCULAR SYSTEMS
  SUSTAINABLE AND CIRCULAR SYSTEMS
• Francesco Pavarelli. Programme in Energetica (cycle 40, 2025-in progress)
• Giacomo Buscemi. Programme in Energetica (cycle 38, 2022-in progress)
• Rocco Giudice. Programme in Energetica (cycle 38, 2022-in progress)

• Piscitelli, M. S.; Mazzarelli, D. M.; Capozzoli, A. (2020)
  Enhancing operational performance of AHUs through an advanced fault detection and diagnosis process based on temporal association and decision rules. In: ENERGY AND BUILDINGS, vol. 226. ISSN 0378-7788
  Contributo su Rivista
• Piscitelli, MARCO SAVINO (2020)
  Enhancing energy management in buildings through data analytics technologies. relatore: CAPOZZOLI, ALFONSO; PERINO, MARCO; , 32. XXXII Ciclo, P.: 219
  Doctoral Thesis
• Pinto, G.; Capozzoli, A.; Piscitelli, M. S.; Savoldi, L. (2020)
  The impact of stakeholder preferences in multicriteria evaluation for the retrofitting of office buildings in Italy. In: 11th International Conference on Sustainability and Energy in Buildings, SEB 2019, Budapest (HUN), 4th -5th July 2019, pp. 581-591. ISSN 2190-3018. ISBN: 978-981-32-9867-5
  Contributo in Atti di Convegno (Proceeding)
• Brandi, S.; Piscitelli, M. S.; Martellacci, M.; Capozzoli, A. (2020)
  Deep reinforcement learning to optimise indoor temperature control and heating energy consumption in buildings. In: ENERGY AND BUILDINGS, vol. 224. ISSN 0378-7788
  Contributo su Rivista
• Piscitelli, M. S.; Brandi, S.; Capozzoli, A. (2019)
  Recognition and classification of typical load profiles in buildings with non-intrusive learning approach. In: APPLIED ENERGY, vol. 255. ISSN 0306-2619
  Contributo su Rivista
• Attanasio, Antonio; Piscitelli, Marco; Chiusano, Silvia; Capozzoli, Alfonso; ... (2019)
  Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates. In: ENERGIES, vol. 12, pp. 1273-1297. ISSN 1996-1073
  Contributo su Rivista
• Capozzoli, Alfonso; Serale, Gianluca; Piscitelli, MARCO SAVINO; Grassi, Daniele (2017)
  Data mining for energy analysis of a large data set of flats. In: PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS. ENGINEERING SUSTAINABILITY, pp. 1-16. ISSN 1478-4629
  Contributo su Rivista
• Capozzoli, Alfonso; Piscitelli, Marco Savino; Brandi, Silvio (2017)
  Mining typical load profiles in buildings to support energy management in the smart city context. In: ENERGY PROCEDIA, vol. 134, pp. 865-874. ISSN 1876-6102
  Contributo su Rivista

• PROCESSO PER LA PREVISIONE ORARIA CON ORIZZONTE TEMPORALE DI 24H DELLA DOMANDA DI POTENZA ELETTRICA DEGLI EDIFICI BASATO SULL'UTILIZZO DI TECNICHE DI DEEP LEARNING. national Software
  Inventors: Silvio Brandi Alfonso Capozzoli Marco Savino Piscitelli