I am interested in modelling and managing complex, non-linear systems—such as energy grids—under environmental stressors. I hold a Geoscientist-in-Training (GIT) license, earned through a BSc in Geoscience (specialist) and Climatology (minor) from the University of Toronto (2023), where I conducted research on the physical impacts of climate change across sectors including energy, agriculture, glaciology, and oceanography.
I completed an MSc in Sustainability, Enterprise and the Environment at the University of Oxford (2024), focusing on the intersection of environmental science, data-driven decision-making, and policy.
Currently, I am pursuing a PhD in Engineering Science at the University of Oxford, affiliated with the Intelligent Earth Centre for Doctoral Training in Artificial Intelligence for the Environment. My research focuses on integrating Observation data with deep reinforcement learning (DRL) techniques to enable adaptive planning and optimisation in dynamic environmental systems. Specifically, I am developing DRL-based control and planning models to improve downstream decision tasks for power grids such as resource allocation, resilience forecasting, and sustainable infrastructure planning. As a visiting researcher, I am eager to explore various ways of leveraging DRL and EO technologies to enhance environmental resilience.
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