Zoe Kexin Xie
Doctoral Researcher
UCL
Kexin (Zoe) joined EBRE after completing her undergraduate degree in BSc (HONS) in Building Engineering and Management with a minor in Applied Mathematics at the Hong Kong Polytechnic University. During her undergraduate studies, she conducted research on the application of Personal Cooling Devices before developing a keen research interest in energy demand modelling.
Physics-informed Bottom-up Machine Learning Flexibility Prediction for Building Cluster
Her recent research primarily focuses on predicting building demand flexibility using machine-learning approaches, under the guidance of Dr. Rui Tang and Dr. Dimitros Rovas.
In the pilot project, Zoe developed a theoretical model to identify the key building factors affecting building energy demand flexibility and a sensitivity analysis surrounding the key factors identified with 65536 Energyplus models. On top of the results, she is currently focusing on developing a systematic method for predicting energy demand flexibility for UK buildings, ultimately contributing to a more sustainable and efficient energy management approach.