Building thermal dynamics modeling with deep learning exploiting large residential smart thermostat dataset. - Han Li 013; Giuseppe Pinto; Alfonso Capozzoli; Tianzhen Hong (BuildSys, 2022)

Data-Driven Key Performance Indicators and Datasets for Building Energy Flexibility: A Review and Perspectives. - Han Li 013; Hicham Johra; Flavia de Andrade Pereira; Tianzhen Hong; Jérôme Le Dreau; Anthony Maturo; Mingjun Wei; Yapan Liu; Ali Saberi-Derakhtenjani; Zoltán Nagy 002; Anna Marszal-Pomianowska; Donal Finn; et al. (CoRR, 2022)

CityLearn v2: An OpenAI Gym environment for demand response control benchmarking in grid-interactive communities. - Kingsley Nweye; Kathryn Kaspar; Giacomo Buscemi; Giuseppe Pinto; Han Li 013; Tianzhen Hong; Mohamed Ouf; Alfonso Capozzoli; Zoltán Nagy 002 (BuildSys, 2023)

CityLearn v2: Energy-flexible, resilient, occupant-centric, and carbon-aware management of grid-interactive communities. - Kingsley Nweye; Kathryn Kaspar; Giacomo Buscemi; Tiago Fonseca; Giuseppe Pinto; Dipanjan Ghose; Satvik Duddukuru; Pavani Pratapa; Han Li 013; Javad Mohammadi; Luis Lino Ferreira; Tianzhen Hong; et al. (CoRR, 2024)

Building thermal dynamics modeling with deep transfer learning using a large residential smart thermostat dataset. - Han Li 013; Giuseppe Pinto; Marco Savino Piscitelli; Alfonso Capozzoli; Tianzhen Hong (Eng. Appl. Artif. Intell., 2024)