Making Her Mark in STEAM: Meet Qinyi

This International Day of Women in Mathematics, we are sharing the story of Qinyi – an inspiring alumna making her mark in STEAM.

Since graduating from Marymount with an IB score of 45, including 7 points in Further Mathematics as an additional subject, Qinyi has earned a First Class Honours Bachelor of Science in Mathematics from Imperial College London. She subsequently pursued postgraduate study at the University of Oxford, achieving a Distinction in her MSc in Applied Statistics and a DPhil (PhD) in Statistics, specialising in statistical machine learning. Her doctoral studies were fully funded by the Engineering and Physical Sciences Research Council (EPSRC).

A former Marymount Valedictorian and ranked among the top 0.23% of IB candidates worldwide, she recently returned to share her academic journey with students, explain how she found her way into statistical machine learning, and offer advice and insights into the field.

Dr Qinyi Zhang (Class of 2011)

Life Since Marymount

From arriving at Marymount with little English, Qinyi went on to become a highly accomplished academic, mathematician and statistician. Though currently based in London, she has presented her research at international conferences, including ‘Women in Machine Learning NeurIPS’ in Barcelona, ‘Uncertainty in Artificial Intelligence’ in Sydney, and ’Recent Developments in Kernel Methods’ in London.

In conversation with Qinyi

What inspired your interest in these fields?

Driven by a curiosity to understand the world, I was drawn to mathematics, probability, and statistics, which eventually led me to machine learning. I find it hugely rewarding to collaborate with exceptional individuals, studying models that can be applied to real-world challenges and make a difference. Studying maths at university provided me with a firm theoretical foundation, enabling me to understand complex models, improve them and apply them in areas where we can see a tangible impact.

What is a project, innovation, or piece of work you’re most proud of?

I am most proud of my work with my collaborators, “Large-Scale Kernel Methods for Independence Testing”, which was published in the journal Statistics and Computing. We scaled up the powerful kernel independence test using various approximation methods, enabling its application to large-scale settings that were previously computationally infeasible. Applications to real and synthetic data experiments have shown that our proposed approximation significantly reduces computational time and memory while providing comparable performance.

How did Marymount influence your interest in STEAM?

Before coming to Marymount, I had never considered studying maths as a possible path. Being in an all-girls school provided a safe and supportive environment, free from distractions, where I could fully explore my natural interests. The school offered a sense of calm and tranquillity that helped ease the pressures and comparisons often felt at such an impressionable age.

I joined Marymount from a co-educational school in China, speaking little English, and quickly became part of a close-knit, international community. The school not only supported my language development but also celebrated cultural differences. I never felt out of place—Marymount reflected the real world, where everyone is unique and follows their own path.

Were there any teachers, activities, or moments that shaped your journey?

I am deeply grateful to Mr Ripp, who had a significant influence on my academic path. He inspired me to pursue mathematics beyond high school, and through his teaching of Further Maths, equipped me with the knowledge and confidence that supported me in my first year of undergraduate study.

What advice would you give to current Marymount students interested in STEAM?

Dedicate yourself to mastering your chosen field, whether it’s maths, computer science, engineering, or another STEAM subject. Believe in your potential and keep improving. With consistent effort over a few years, you can make remarkable progress and unlock countless opportunities.

What’s one thing you wish you had known when you were in school?

The support available to you at school is immense—and it won’t always be like this. Make the most of it. Trust your teachers, learn from their experience, and lean on your peers for support and guidance. Use every available resource and appreciate the strength of the community around you.

What does the future hold?

Besides raising my young son, I am currently privately tutoring students. I would eventually like to return to full-time work applying cool machine learning algorithms to real-world problems.

Dr Qinyi Zhang is available for private tutoring. Find out more and get in touch with her here!