Out-of-Distribution Data Fitting
- Designed splitting strategies that emulate real-world distribution shift.
- Benchmarked state-of-the-art ML/DL models under shifted data regimes.
I teach machines to reason over graphs — and I'm chasing brain-like models that move us closer to genuinely human-like AI. Optimization is where it all begins.
Open to research & roles
I'm an undergraduate in Artificial Intelligence at Deakin University, driven by curiosity and a deep love of mathematics. My work lives where optimization meets graph neural networks — the geometry of how information flows across structured data.
Increasingly, I'm drawn to neuroscience-inspired models such as brain-like neural networks, which I believe are indispensable to building AI that genuinely resembles human reasoning.
Before university, I trained as a competitive programmer, picking up a strong foundation in data structures and algorithms — and a habit of chasing problems all the way to their mathematical core.
A full breakdown of the questions I find worth chasing lives on the research page.