I was supposed to be a doctor.

I grew up in northern Nigeria, moving from state to state as my father's banking career took our family across the region. It was a childhood of constant adjustment — new schools, new friends, new cities — but mathematics was always the same everywhere I went. Reliable, consistent, and somehow mine.

When I was admitted to Bayero University Kano to study medicine, it felt like the natural destination. Medicine was prestigious, purposeful, the kind of career that made sense to everyone around me. I had worked hard to get there.

But at the point of registration, everything changed. The circumstances that day meant I could not proceed with medicine. I was redirected to mathematics.

I was not happy about it.

What I did not know then

I did not know that mathematics would take me further than medicine ever could have — at least the version of medicine I had imagined for myself. I did not know that equations could describe the behaviour of tumours, that computation could simulate how cancer responds to drugs, that a mathematician could contribute meaningfully to the fight against one of the world's most complex diseases.

I did not know any of that at the registration desk in Kano, frustrated and uncertain about a future that had just been rewritten without my permission.

What I did know, within months of starting, was that I loved it. The rigour, the elegance, the way a well-constructed proof felt like a small act of creation. Mathematics rewarded persistence and precision — two things I had developed during years of moving schools and starting over.

The long road

My path after BUK was not straight. I studied information technology, then pure and applied mathematics at postgraduate level. I worked in government — at the Federal Inland Revenue Service, the Securities and Exchange Commission, the Standards Organisation of Nigeria. I taught mathematics in classrooms with too many students and not enough resources.

None of it was wasted. The government work taught me how institutions function and how data drives decisions. The teaching taught me how to explain complex ideas simply — a skill that turns out to be essential in research. The mathematics underpinned all of it.

In 2022 I received a scholarship to pursue a PhD at the University of Birmingham. The focus: mathematical and computational modelling of tumour growth. AI-driven approaches to understanding how cancer behaves, responds to chemotherapy, and adapts under stress.

The girl who was supposed to study medicine is now building mathematical models that could one day help personalise cancer treatment. Fate, it turns out, had a longer plan than I did.

What this journey taught me

I have learned that disruption is not the same as failure. The moment at that registration desk felt like a door closing. It was actually a door opening — to a field I did not know existed, to a career I could not have imagined, to a version of myself I had not yet met.

If you are early in your journey — uncertain, redirected, wondering whether the path you are on is the right one — I want you to know that the destination is not always visible from the starting point. Sometimes you have to trust the mathematics of the situation: that the variables you cannot yet see will, in time, resolve into something meaningful.

Mine did. And I am still enjoying the journey.