As an early career postdoc I have two major goals: to continue finding and publishing new results that expand from the work in my PhD thesis, and to branch out into new fields and find new collaborations. The second task can be especially rewarding, because it allows me to translate skills learned during my PhD studies into exciting new domains and it provides opportunities to find new research buddies.

Tell us a little about your background and education.

Growing up, my family was quite nomadic and I suppose my education has been as well. I began undergrad at the University of Regina in the petroleum engineering program, switched to electrical engineering and dabbled in writing apps for iPhones, switched to a math and physics double major, then switched to honours math. I had work terms at a fertilizer plant in Saskatchewan, a particle accelerator in Vancouver, and two summer research projects in pure math.

I completed my PhD at the University of Toronto, which really required me to settle down and focus on one thing, but I am still a nomad when it comes to research. Who knows what you will discover in the next book on the next shelf? It's an adventure!

When did you decide to make a career in mathematics?

Back in engineering, I remember being struck in linear algebra class by how powerful and elegant mathematics could be: with the right rules in hand (e.g. associativity), one could prove very general facts about matrices with only a couple symbols. Abstraction felt natural and really appealed to me.

My Calculus II professor Bruce Gilligan told me, the Summer after the class had ended, that I should consider pursuing a PhD in math. It was several years until I decided to abandon engineering, but that encouragement really stuck with me. I've been incredibly lucky in terms of finding great mentors early-on. Bruce Gilligan, Don Stanley, and Yael Karshon (my PhD advisor) are great mathematicians and wonderful people.

What do you do when you are not working? What are your hobbies and other interests?

I like honing new skills. In graduate school I spent a lot of time in the camera club's darkroom making prints of the same negative over and over until I was completely satisfied.

Right now I am working on baking bread and machine learning/ai. There are a lot of similarities: for each you have a general recipe, but simply following the recipe is not enough to get a really good result. There is an art that can only be learned through experience. It's very intuitive.