I first started programming a decade ago in Computational Physics classes at university.

In some of those classes, we’d write small C programs to generate a list of points to plot on a graph.

In one of those classes, I increased a loop iteration 100-fold and sat back in awe. My computer crunched numbers and generated a plot so dense with points that I realized I could spend a lifetime trying to replicate it by hand and never come close.

That day lit a spark in me. I can trace a clear line from that moment to where I am today.

For a kid who couldn’t build with his hands or draw with a pencil, programming gave me the ability to create with my thoughts.

I’ve found that the problems I enjoy working on most are “performance” related in some way or another.

Whether it’s identifying and reducing areas of high memory use, or making things go faster, I always get a kick out of understanding complex systems and making them better.

Generally, optimising for performance requires understanding what a program is really doing, so I like to think that the physicist in me stayed around in that regard.