Introducing Stuart
Stuart is a Research Data Specialist at MDAP, passionate about bioinformatics, data visualisation, and tackling complex biological challenges. An avid learner and gardener, he also enjoys exploring new cultures, having recently studied Spanish in Mexico. Dedicated to advancing data curation and exploration, Stuart aims to brudge the gap between research and real-world impact.
Tell us a bit about your career trajectory so far
The path to my career has been a guided random walk-through work that I find interesting and challenging. I started off studying maths in Adelaide and discovered that I really enjoyed statistics, which to me is a perfect combination of computation, creativity, and problem solving.
After my bachelor's I moved over to Canberra for a short stint working in the public service and then I left for slightly warmer climates in Melbourne to start a Masters in Bioinformatics, where I did a research project on understanding the selction pressure on malaria parasites across the world. I discovered I had a knack for data visualisation which led me to a PhD at Monash Uni combining my interests in biology, statistics, and visualisation all at once!
The write up phase of my PhD coincided with the beginning of the pandemic, and I was very fortunate to find a remote job at this time for a US based biotech firm where I made web apps to help scientists interrogate clinical trial data.
I find it difficult to specialise as there are so many fascinating things out there to learn about and do, which is why when the role at MDAP came up I had to apply!
Tell us about an interesting project you're working on at MDAP
My main project at MDAP is developing a website (in collaboration with Prof. Christine Wells) to help researcher, patients, and policy makers discover and register stem cell lines that have been created in Australia. Stem cell lines are pivotal biological models for performing experiments that help unravel our understanding of diseases.
Currently, there is no centralised location based in Australia that provides information about the provenance and details of our cells lines, having one would be a great boon to the stem cell research community as well as patients and disease advocacy groups.
This has been a challenging project to work on as there are so many moving parts: data governance and ethics (a lot of stem cell lines are produced from donors), user experience and design (how can we make the process of finding information on our site as painless as possible), and the biology (stem cells are complex and have lots of interrelated parts so we need to figure out what is important!).
What are some of the solvable, difficult, or wicked problems on your horizon?
Keeping up with the pace of changes in areas like large language models, as well of all the technologies our team uses is a challenge. It feels like a bit of a wild west sometimes, but it is a great privilege to have a job that allows me to always be learning new things!
Outside of work , I am trying to get my balcony garden going but so far I seem to kill everything!
Can you tell us about your latest adventure or next planned one outside of MDAP?
During the pandemic I started learning Spanish online with zero prior experience and when things opened up again, I took the opportunity to visit Mexico for some intensive language study. I went to San Cristóbal de las Casas in Chiapas which is home to Mexico's coffee and cacao farms, as well as the Zapatista movement for Indigenous rights. It was a really beautiful trip and challenging to use Spanish in context (at first, I thought everyone talked so quickly!) but I made some great friends there so of course I am very keen to go back and travel with them throughout Central and South America. ¡Vamos!
In the context of a rapidly evolving global environment and UoM's research strategy, what would you like to explore, challenge, or innovate in your work in the future?
I think data curation and exploration is an underrated and complex part of any data intensive project. Data curation refers to the process of gathering data from different sources and combining and cleaning them into a form that helps answer a research question and is deeply intertwined with exploration (exploratory data analysis or EDA) which is the process of looking at the data and trying to find pattern.
There are many possible decisions (garden of forking paths problem) that you have to make during this process which can ultimately effect whenat you might learn from the data. Doing this in a robust way while acknowledging the uncertainity introduced by the decisions we have made is something that I want to explore more. Always look at your data!