Lei Liu

Higher Degree Research


LEI is in his second-year doctoral candidate, focusing on building energy consumption estimation and prediction and life cycle energy assessment (LCA). He has diversified experience and knowledge in construction management, green building, and health building. His skill sets include machine learning, factor analysis, and numerical and analytical modelling. He is passionate about carbon neutrality achievement and residential building sustainable development.


Predicting the Life Cycle Energy Consumption of Residential Buildings based on Rebound Effects and Policy Optimisation

  • Project Image

Developing an extended life cycle energy boundary of buildings and a rebound effect-based model to predict building energy consumption in the next few decades. It will enrich the theoretical knowledge of the life cycle assessment and provide a new pathway to reduce energy consumption prediction errors. Meanwhile, the prediction value and policy optimisation schemes can be as valuable references for policymakers, practitioners, as well as other developing countries with similar background.