– ABOUT ME
Physicist.
Developer.
Perpetual student.
I’m Julia – a computational physics PhD student who came to science later than most, via insurance and finance, with four kids in tow. I simulate magnetic systems, write GPU-accelerated code in Julia, and share what I learn so others don’t have to figure it out alone.
BASED IN
Canada
RESEARCH
Nanomagnetism
LANGUAGES
Julia, Python
01 – ORIGIN STORY
From spreadsheets to Schrödinger.
Before I ever wrote a line of code or ran a Monte Carlo simulation, I was in insurance and finance – crunching numbers, sitting in meetings, making phone calls, meeting clients. It was fine. It just wasn’t quite right.
In 2017, at 33 and with a toddler on my hip, I swapped spreadsheets and emails for Schrödinger’s equation. More accurately, Maxwell’s equations – but you get the idea.
“Confidence comes slowly. Seven years after starting this journey, I finally earned my MSc. Impostor syndrome still knocks on the door, but I remind myself: if I’ve come this far, it was earned.”
For years I hesitated to put my thoughts out there. I doubted whether I had anything worthwhile to share. Now, over a year into my PhD, I can feel myself growing into this role – and this site is part of that.
02 – WHAT I DO NOW
Simulating tiny magnets. At scale.
These days I simulate magnetic nanoparticle assemblies using high-performance computing. I’m interested in spin glass physics systems where particles interact in frustrated, disordered ways that produce surprisingly rich behaviour.
My main tool is SpinGlassLab, a Julia package I’m building for my PhD, which runs Monte Carlo simulations using custom CUDA kernels. When your simulation needs to run thousands of times to gather statistics, every millisecond matters.
When I’m not debugging simulations or working through the physics, I’m writing blog posts, making YouTube videos, or reading something completely unrelated to science.
03 – WHAT THIS SITE IS
The notes I wish I’d had.
This site is where I share what I learn along the way – from Linux workflows to GPU programming, from research reflections to moments of self-doubt. The honest version of the journey, not just the highlight reel.
Sharing what I’ve learned feels right. Maybe a tip here saves you an afternoon of debugging. Maybe a story there sparks someone’s next idea. Science only matters when we pass it on.
If any part of that resonates with you – welcome. You’re in the right place.
04 – WHAT YOU’LL FIND
The topics I keep coming back to.
Linux workflows and tooling for technical work
Research notes and reflections from the PhD
Personal stories from a non-traditional path into science
GPU programming and HPC in Julia, with custom CUDA kernels
Coding walkthroughs and development logs
Occasional tangents, metaphors, and digital coffee
Want to follow the journey?
The newsletter goes out when there’s something worth saying – new posts, honest reflections, and the occasional update from the simulation queue.