Research background
Xiang Xie is a research associate working in the Asset Management group in Institute for Manufacturing. Xiang’s research mainly focuses on the application of building level and campus level Digital Twin to support better-informed decision-making. Particularly, he is interested in establishing a digital-twin enabled building energy quantification and performance assessment framework in Operations and Maintenance management.
CDBB projects involved with
West Cambridge Digital Twin Facility
Research ambitions for CDBB
My research in CDBB will focus on demonstrating the role Digital Twin plays in delivering public benefits, unlocking the value from data and providing determinable insights for construction sector, during the operation and maintenance management. In particular, I am working on developing a fault diagnosis/prognosis system that exploits machine learning capabilities to detect anomalies of energy assets, and facilitates understanding of their interaction with indoor built environment. Meanwhile, I would also actively explore an appropriate energy quantification and assessment framework to ascertain the efficiency of energy use in buildings and lay the foundation for decision-making to enhance energy efficiency.
