Researcher by day, hobbyist by every other hour. This is the slightly more personal version — the papers live on the research page.
I'm a PhD candidate in the Faculty of IT at Monash Universityin Melbourne, where I work on multi-agent path finding — figuring out how dozens or hundreds of robots, drones, and vehicles can move through the same space at once without colliding, deadlocking, or wasting a second. It sits right where I like to be: equal parts clean mathematics and messy real-world engineering.
I didn't start in computer science theory. My background is inengineering and advanced computer science, and I spent years building things that had to actually work — flight-control algorithms for drones, a full-stack tool used by medical professionals, and more small automation projects than I can reasonably list. That maker's instinct still drives everything I do; I'm happiest when an idea ends up as something running on a screen or in the air.
These days my work splits between two threads: the geometry-and-search world of path finding, and a line of applied research onlarge language models in healthcare — summarising and translating clinical consultations in ways that are actually safe to put in front of patients. The common thread is a soft spot for problems where getting it almost right isn't good enough.
I teach across both AI and electrical-engineering units, and I help organise the international Workshop on Multi-Agent Path Finding — which means I get to spend time with the people whose papers I grew up reading. Outside the university I've been riding bikes for nearly a decade, I practise Chinese calligraphy, I keep flying drones for fun, and I share my desk with a cat who is entirely unimpressed by all of it. You can see more of that on the life page.
Always happy to talk path finding, teaching, or a good cycling route —drop me a line.