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