Junemo Koo 
- (2025): Analysis of ventilation and infiltration rates using physics-informed neural networks: Impact of space operation and meteorological factors. In: Building and Environment, v. 267 (Januar 2025).
- (2024): Hybrid models of machine-learning and mechanistic models for indoor particulate matter concentration prediction. In: Journal of Building Engineering, v. 86 (Juni 2024).
- (2023): Ventilation strategy for simultaneous management of indoor particulate matter and airborne transmission risks – A case study for urban schools in South Korea. In: Building and Environment, v. 242 (August 2023).
- (2022): Development and validation of a dynamic mass-balance prediction model for indoor particle concentrations in an office room. In: Building and Environment, v. 207 (Januar 2022).
- (2021): Estimation of the real-time infiltration rate using a low carbon dioxide concentration. In: Journal of Building Engineering, v. 42 (Oktober 2021).
- (2017): Automated processes of estimating the heating and cooling load for building envelope design optimization. In: Building Simulation, v. 11, n. 2 (Oktober 2017).
- (2015): A systematic approach for energy efficient building design factors optimization. In: Energy and Buildings, v. 89 (Februar 2015).
- (2016): A bi-directional systematic design approach to energy optimization for energy-efficient buildings. In: Energy and Buildings, v. 120 (Mai 2016).
- (2017): Impacts of building envelope design factors upon energy loads and their optimization in US standard climate zones using experimental design. In: Energy and Buildings, v. 141 (April 2017).
- (2018): Energy-cost analysis of HVAC system for office buildings: Development of a multiple prediction methodology for HVAC system cost estimation. In: Energy and Buildings, v. 173 (August 2018).
- (2020): Identifying stack-driven indoor environmental problems and associated pressure difference in high-rise residential buildings: Airflow noise and draft. In: Building and Environment, v. 168 (Januar 2020).
- (2019): Meta-models for building energy loads at an arbitrary location. In: Journal of Building Engineering, v. 25 (September 2019).
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