Jack Ngarambe 
- (2023): Coupling convolutional neural networks with gated recurrent units to model illuminance distribution from light pipe systems. In: Building and Environment, v. 237 (Juni 2023).
- (2023): Energy-efficient virtual sensor-based deep reinforcement learning control of indoor CO2 in a kindergarten. In: Frontiers of Architectural Research, v. 12, n. 2 (April 2023).
- (2022): A review on the current usage of machine learning tools for daylighting design and control. In: Building and Environment, v. 223 (September 2022).
- (2022): Geographically extended occupant clothing behavior model using convolutional neural networks with hyperband technique. In: Journal of Building Engineering, v. 49 (Mai 2022).
- (2021): Influences of wind speed, sky conditions, land use and land cover characteristics on the magnitude of the urban heat island in Seoul: An exploratory analysis. In: Sustainable Cities and Society, v. 71 (August 2021).
- (2018): Light pollution: Is there an Environmental Kuznets Curve?. In: Sustainable Cities and Society, v. 42 (Oktober 2018).
- (2020): The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls. In: Energy and Buildings, v. 211 (März 2020).
- (2019): Prediction of indoor clothing insulation levels: A deep learning approach. In: Energy and Buildings, v. 202 (November 2019).
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