- Jianli Chen, Xinghua Gao, Yuqing Hu, Zhaoyun Zeng & Yanan Liu (2019). A meta-model-based optimization approach for fast and reliable calibration of building energy models. Energy. Published, 08/30/2019.
- Jianli Chen, Gail Brager, Godfried Augenbroe & Xinyi Song (2018). Impact of Outdoor Air Quality on the Natural Ventilation Usage of Commercial Buildings in the US. Applied Energy. Published, 11/20/2018.
- Jianli Chen, Godfried Augenbroe & Xinyi Song (2018). Light-weighted Model Predictive Control for Hybrid Ventilation Operation Based on Clusters of Neural Network Models. Automation in Construction. Published, 02/22/2018.
- Jianli Chen, Godfried Augenbroe & Xinyi Song (2017). Evaluating the Potential of Hybrid Ventilation for Small to Medium sized Office Buildings with Different Intelligent Controls and Uncertainties in US Climates. Energy and Buildings. Published, 12/05/2017.
- Jianli Chen, Godfried Augenbroe, Qinpeng Wang & Xinyi Song (2017). Uncertainty Analysis of Thermal Comfort in a Prototypical Naturally Ventilated Office Building and Its Implications Compared to Deterministic Simulation. Energy and Buildings. Published, 04/27/2017.
As a building scientist who is endeavoring to enhance human living conditions, I am enthusastic in improving building and urban intelligence through computing and statistical techniques. This intelligence includes sustainability with energy efficiency and renewable energy integration, robustness with resilience and stable performance, and human-centered services with personalization and improvements tailored to occupants’ needs. Currently, the architecture, engineering, and construction (A/E/C) industry lags behind in adapting to the rapid development of computing power and new techniques, which are capable of dramatically benefitting building stakeholders in numerous ways.