- A case-control study of behavioural and built environment determinants of COVID-19 transmission in sheltered markets. In: Building and Environment, v. 264 (October 2024). (2024):
- Occupancy-based energy consumption modelling using machine learning algorithms for institutional buildings. In: Energy and Buildings, v. 252 (December 2021). (2021):
- A time-based analysis of the personalized exhaust system for airborne infection control in healthcare settings. In: Science and Technology for the Built Environment, v. 21, n. 2 (February 2015). (2015):
- Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks. In: Energy and Buildings, v. 121 (June 2016). (2016):
- Review of occupancy sensing systems and occupancy modeling methodologies for the application in institutional buildings. In: Energy and Buildings, v. 121 (June 2016). (2016):
- Energy performance model development and occupancy number identification of institutional buildings. In: Energy and Buildings, v. 123 (July 2016). (2016):
- Time series forecasting for building energy consumption using weighted Support Vector Regression with differential evolution optimization technique. In: Energy and Buildings, v. 126 (August 2016). (2016):
- Predicting the CO2 levels in buildings using deterministic and identified models. In: Energy and Buildings, v. 127 (September 2016). (2016):
- k-Shape clustering algorithm for building energy usage patterns analysis and forecasting model accuracy improvement. In: Energy and Buildings, v. 146 (July 2017). (2017):
- Anthropogenic heat reduction through retrofitting strategies of campus buildings. In: Energy and Buildings, v. 152 (October 2017). (2017):
- Bayesian calibration of building energy models with large datasets. In: Energy and Buildings, v. 154 (November 2017). (2017):
- Comparison of different occupancy counting methods for single system-single zone applications. In: Energy and Buildings, v. 172 (August 2018). (2018):
- On the potential of building adaptation measures to counterbalance the impact of climatic change in the tropics. In: Energy and Buildings, v. 229 (December 2020). (2020):
- Energy efficient HVAC systems. In: Energy and Buildings, v. 179 (November 2018). (2018):
- (2019): Building Energy Consumption Raw Data Forecasting Using Data Cleaning and Deep Recurrent Neural Networks. In: Buildings, v. 9, n. 9 (22 August 2019).
- Energy utilizability concept as a retrofitting solution selection criterion for buildings. In: Journal of Civil Engineering and Management, v. 23, n. 5 (May 2017). (2017):