Research Assistant, Life Cycle Management Lab, The University of British Columbia
– Development of a reinforcement learning (RL)-based smart building control framework for residential buildings. Mar. 2022 – Present
- Develop a virtual simulation testbed for smart building control using EnergyPlus and Python.
- Develop a BuildingLearn-Open AI Gym Environment for implementing reinforcement learning-based smart building control.
- Propose an RL-based control framework to learn the interactions between occupants, building HVAC systems, and the environment.
– Development of a community-level energy retrofits decision support framework.
May. 2020 – Dec. 2021
- Identified archetypes of existing residential buildings with high GHG emissions;
- Developed building energy models (HOT2000) to calculate energy consumptions and emissions of retrofit measures for residential buildings;
- Performed life cycle assessment and life cycle costing of retrofit measures for residential buildings;
- Investigated trade-offs of environmental and economic impacts for retrofit decision-making;
- Proposed a multi-objective optimization framework to identify optimal retrofit solutions;
- Developed an artificial neural network to predict building energy consumption using Python;
- Presented the research work to industry people and drafted a final project report.
- Drafted a paper and published it in a prestigious international journal
– Research on policy strategies for implementing energy retrofits in the residential buildings.
Sept. 2019 – Mar. 2021
- Examined a multitude of retrofit policy instruments for residential buildings across different countries;
- Developed a classification framework to characterize different kinds of policy instruments;
- Identified the policy coverage, practice, and barriers to the uptake of retrofit schemes;
- Proposed policy recommendations for the penetration of retrofit schemes.
- Drafted a paper and published it on a prestigious international journal