Mark Girard

About me

I’m a mathematician who loves finding solutions to tough mathematical problems! I’m currently a data scientist at Geotab, where I leverage Geotab’s trove of telematics data from electric vehicles to make machine learning models that learn how much energy they use and how to make driving trips more efficient.

I earned a PhD in Mathematics from the University of Calgary (2017), where I researched applications of convex analysis to quantum information theory (specifically entanglement theory) under the supervision of Gilad Gour. Afterward I was a postdoctoral researcher at the Institute for Quantum Computing at the University of Waterloo (2017-2020) under the supervision of John Watrous.

I enjoy mathematical challenges! I have recently gotten into solving 538’s Riddlers and started compiling my solutions here.

Outside of mathematics, I enjoy playing ultimate frisbee, homebrewing beer, tabletop games, and various outdoor activities (hiking, camping, climbing, skiing, snowshoeing).

Research

When I was still in academia, my research interests centred around solving mathematical problems motivated by questions in quantum information theory. I primarily made use of convex analysis, convex optimization, linear algebra, matrix analysis, and operator algebras to tackle questions related to the theory of quantum entanglement.

See a list of my publications here and more details of my research here.

Miscellaneous

• Teaching I’ve taught numerous courses during my time as an academic.

• Lecture notes and problem solutions TeX’ed up lecture notes and solutions to problem sets of the courses that I took during my graduate studies. You can see the list of courses here.