I'm a Machine Learning Engineer with a focus on model efficiency, inference systems, and applied deep learning - particularly in domains where the work has real-world consequences: environmental monitoring, healthcare, and scientific research.

Currently, I work as an AI Engineer at Channelscaler, where I engineered the backend of Scailyn — the platform's first production AI agent — implementing the tool-use framework and RAG architecture that is now being extended across teams, with the agent set to become the primary interface for platform users.

I hold First-Class Honours MEng and BEng degrees in Electronic and Computer Engineering from Trinity College Dublin, with strong foundations in signal processing, linear algebra, and optimisation. My MEng thesis extended CycleGAN for day-to-night image translation, achieving a 20% improvement on Kernel Inception Distance through a novel timestamp conditioning architecture.

Outside of work, I'm building Mamba-RS-Engine — a C++/TensorRT inference engine for satellite imagery change detection using State Space Models, targeting wildfire and flood monitoring applications. Alongside this, I maintain a range of personal projects spanning agentic AI experiments, web development, and photography.