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Energy System Modelling & Optimization:
Developing robust, adaptive models to simulate and optimise complex energy systems under uncertainty. -
Decarbonisation Strategies:
Investigating the role of renewable energy sources, including green hydrogen and hydropower, in achieving low-carbon energy systems, with applications in both high-risk and low- and low-income countries. -
Machine Learning for Uncertainty & Risk Quantification:
Creating and integrating ML modules—such as Bayesian neural networks, unsupervised anomaly detection, and reinforcement learning—into simulation loops to dynamically adjust model parameters in response to evolving risks (e.g., war-induced infrastructure damage).
This repository contains my research code, projects, and papers related to advanced energy system modelling and machine learning applications in the energy sector.