- (2024): Perspectives of Machine Learning and Natural Language Processing on Characterizing Positive Energy Districts. Dans: Buildings, v. 14, n. 2 (1 février 2024).
- (2023): ChatGPT for Fast Learning of Positive Energy District (PED): A Trial Testing and Comparison with Expert Discussion Results. Dans: Buildings, v. 13, n. 6 (23 mai 2023).
- (2021): A Top-Down Digital Mapping of Spatial-Temporal Energy Use for Municipality-Owned Buildings: A Case Study in Borlänge, Sweden. Dans: Buildings, v. 11, n. 2 (20 janvier 2021).
- A review of reinforcement learning methodologies for controlling occupant comfort in buildings. Dans: Sustainable Cities and Society, v. 51 (novembre 2019). (2019):
- A novel reinforcement learning method for improving occupant comfort via window opening and closing. Dans: Sustainable Cities and Society, v. 61 (octobre 2020). (2020):
- (2020): An Approach to Data Acquisition for Urban Building Energy Modeling Using a Gaussian Mixture Model and Expectation-Maximization Algorithm. Dans: Buildings, v. 11, n. 1 (22 décembre 2020).
- A data-driven model predictive control for lighting system based on historical occupancy in an office building: Methodology development. Dans: Building Simulation, v. 14, n. 1 (novembre 2020). (2020):
- Modeling occupant behavior in buildings. Dans: Building and Environment, v. 174 (mai 2020). (2020):
- Development of an adaptation table to enhance the accuracy of the predicted mean vote model. Dans: Building and Environment, v. 168 (janvier 2020). (2020):
- A study on influential factors of occupant window-opening behavior in an office building in China. Dans: Building and Environment, v. 133 (avril 2018). (2018):