Staff Spotlight – Vuong Nguyen



Vancouver – Hippy Lab & Institute for Global Health

Learn more about the inspiring journey and impactful work of Vuong Nguyen, a dedicated researcher with a unique blend of expertise in biology, statistics, and ecological modeling. As a biostatistician with UBC Orthopaedics, working jointly between the Hippy Lab and the Institute for Global Health, Vuong shares insights on the transformative potential of research, the excitement of problem-solving, and the importance of translating academic findings into tangible benefits for patients and communities.

Can you share a little bit about your educational background and journey, and how you got to where you are today?

I did my Bachelor of Science majoring in Biology and Statistics at the University of Sydney. Afterwards, I pursued a PhD doing ecological modelling which allowed me to combine my skills in statistical analysis with my interest in environmental science. Upon submitting my thesis and graduating, I started working for the Save Sight Institute (SSI) at Sydney Eye Hospital as the sole biostatistician in which I was in charge of the statistical analysis and support for the institute, including higher degree medical students. The primary area of research was focused on real-world data analysis in patients with neovascular age-related macular degeneration, one of the leading causes of blindness particularly in developed countries. This was my first exposure to the world of biostatistics, medical data, and clinical trials but I was excited by the prospect of my statistical analysis having real-world impact on patient’s health and quality of life. After 6 years working at SSI, I applied for the position of biostatistician at UBC in mid-2022 working jointly between the Hippy lab and the Institute for Global Health (IGH).

What inspired you to work in research?

During my undergraduate degree, I wasn’t actually sure what it was I wanted to do. However, in my final year of undergraduate studies, one of my professors who later became my PhD supervisor introduced us to matrix population modelling. In 1987, researchers published a paper where they built a matrix population model for the endangered loggerhead sea turtles. Conservation efforts had previously focused on protecting eggs on nesting beaches. The matrix models however demonstrated that the most significant life stages to improve the survival of the sea turtle population was the juveniles and mature stage breeders. This resulted in more widespread use of turtle exclusion devices on fishing nets which allow accidentally captured turtles to escape. This was very eye-opening for me as it was the first time seeing a concrete example of statistics and statistical modelling being applied to solve a real-world problem that resulted in actionable change. Although my PhD was in ecological research, these days, I’m happy to apply to my skillset to advance research in any field that interests me and that has a positive, tangible impact.

What impact would you like to see your work have on patients, communities and society at large?

I’m most interested in having published research in academia translated into actions or changes in behaviour that result in tangible benefits for patients. At IGH for example, we have worked on implementing a prediction model to identify children at risk of mortality after being discharged from the hospital in low-income countries which is very exciting. However, one of the things that I’ve noticed when it comes to prediction models is that a lot of them get published in journals but very rarely do they actually get implemented in practice, and it is even less common that they get evaluated on metrics that actually matter to patients and healthcare providers. Typically, measures of performance for prediction models include things like sensitivity, specificity, AUC, and calibration but ultimately, the goal of our models is to reduce paediatric post-discharge mortality. To that end, we are continuing to collect data on post-discharge mortality following implementation of our prediction models so see what, if any, impact the models have on patients.

What excites you most about your work? What are you most proud of?

I love problem solving so taking on interesting problems from a diverse range of fields is what excites me about my work. I’m also very fortunate in that I have been able to collaborate and work with knowledgeable people from all over the world.

What is one piece of advice that you’d like to give to current trainees?

Don’t be afraid to ask for help or advice – the University is full of resources, people, and workshops that can help if you’re feeling lost or uncertain (including statistical support!)

When you’re not working, where can we find you?

Most days, I’m spending time with my corgi, Gimli, but I love going out to see live music and musical theatre. At home, I enjoy reading, video games, and playing guitar.