Yujie Xu (A 2020)
(she/her)
About
Yujie Xu completed her doctor’s degree in Building Performance & Diagnostics at Carnegie Mellon University. Xu’s PhD research focuses on energy retrofits of existing buildings as a means to reduce building consumption and carbon footprint, specifically concentrating on data-driven approaches “to generalize the heterogeneous treatment effect of past retrofits to future potential savings.” After successfully defending her thesis, “Using Machine Learning to Target Retrofits in Commercial Buildings under Alternative Climate Change Scenarios,” in 2020, Xu is now a Data Scientist in the Building Technology and Urban Systems Department at Lawrence Berkeley National Laboratory.
Publications and Conferences during PhD
Xu, Y., Loftness, V., & Severnini, E. (2021). Using machine learning to predict retrofit effects for a commercial building portfolio. Energies, 14(14), 4334. https://doi.org/10.3390/en14144334
Hong, T., Xu, Y., Sun, K., Zhang, W., Luo, X., & Hooper, B. (2021). Urban microclimate and its impact on building performance: A case study of san francisco. Urban Climate, 38, 100871. https://doi.org/10.1016/j.uclim.2021.100871
Hong, T., Xu, Y., Sun, K., Zhang, W., & Luo, X. (2019, November). Visualizing Urban Microclimate and Quantifying its Impact on Building Energy Use in San Francisco. In Proceedings of the 1st ACM International Workshop on Urban Building Energy Sensing, Controls, Big Data Analysis, and Visualization (pp. 1-5).
Xu, Y., Aziz, A., Lasternas, B., & Loftness, V. (2018). Comparison of data-driven building energy use models for retrofit impact evaluation. In 7th International Building Physics Conference, IBPC2018 (pp. 1157-1162). Syracuse, NY: International Association of Building Physics.