Bridget is a Rhodes Scholar pursuing a DPhil in Mathematics at the University of Oxford, supervised by Professor Renaud Lambiotte and Professor Doyne Farmer.
Her research is focused on developing theoretical tools grounded in information science and network science to model, characterise and assess uncertainty in complex real-world systems.
Bridget applies the outcomes of her research to gain meaningful insights into many systems; currently, she is working to improve prediction quality for economic models and designing better tools to measure temporal relationships in online social networks.
About me
Before moving to the UK, I was based at The University of Adelaide where my research focused on modelling and measuring information flows on online social networks.
I started this research as a Westpac Future Leaders Scholar while studying for my MPhil in Applied Mathematics and Statistics. My thesis titled "Measuring and modelling information flows in real-world networks" was awarded the Dean’s Commendation for Research Thesis Excellence.
Through my research, I am passionate about working with policy and decision-makers, sharing the outcomes of my work to improve our capacity to engage in complex settings.
In 2021, I co-authored the Youth National Security Strategy, check it out here.
Recent highlights
Recently, I was a visiting researcher at the Complexity & Society Lab at the Network Science Institute in NorthEastern in Boston, where I spoke about my recent work on generating dynamics with memory on networks.
I was in Santa Fe for the Postdocs in Complexity Conference and a micro-working group looking at prediction markets, a project which spun out of the 2024 Complexity Global School, preprint coming soon!
In my work looking at economies and financial markets, I'm looking at how we can predict temporal signals while overcoming the bias-variance trade-off with collaborators from INET Oxford. I was an invited speaker at the YSI Focus Session at NetSci 2024 where I spoke about information theoretic estimators in finance.
If you’re interested in my work on online social networks, you can hear me discuss mis- and dis-information on this podcast! Also check out my recent preprint on a more efficient method to estimate LCS for entropy estimation.