About

I am fascinated by the mathematics underlying complex systems that contain cycles or feedback loops (or, what mathematicians may call “higher genus structures”), and the information that cycles encode. Most of my formal work falls under the general classification of operad theory , but my inspiration comes from other areas of mathematics and beyond.

My PhD (Aberdeen, 2018, funded by the Blue Brain Project at the EPFL in Switzerland) was inspired by problems of understanding understanding complex networked structures at multiple scales. This remains the driving motivation of my research: as our reliance on data and AI applications continues to snowball, sophisticated and robust theoretical tools for understanding and interrogating complex networks are ever-more essential.

I love big mathematical challenges. Perhaps unusually, my mathematical elation does not come from finding a solution to a difficult problem, but from figuring out what makes the problem so hard in the first place.

I was six when my primary school teacher, Miss Newport, gave a name to my passion for understanding the patterns and relationships in the world around me: “Mathematics”. She taught me that maths is creative and driven by curiousity for the world, and not a competitive subject concerned only with right answers.

Though I have loved maths all my life, my path to academic research has been long, frequently painful, and largely determined by luck. It is all too obvious that the obstacles that I have faced pale compared with the structural barriers that obstruct participation for many others.

Maths is a universal human activity, and mathematics is created by living, breathing humans, all of us different. I am privileged to have access to mathematical spaces. It is essential that I use my privilege to challenge persisting exclusionary practice, and to help build spaces that are accessible and welcoming to everyone, regardless of background.

Improving our mathematical culture is fundamentally right and necessary. It is surely also the most effective way to increase the quantity, quality, and relevance of new contributions to the body of mathematical knowledge.