Bridget Smart
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Smart, B., Roughan, M. and Mitchell, L. (2024) ‘The entropy rate of Linear Additive Markov Processes’. Available at: https://doi.org/10.48550/ARXIV.2211.05350. PLOS one, 19(4), p.e0295074.
Smart, B. (2023) Measuring and modelling information flows in real-world networks. Thesis. Available here (Accessed: 2 February 2024).
Smart, B. et al. (2022) ‘#IStandWithPutin Versus #IStandWithUkraine: The Interaction of Bots and Humans in Discussion of the Russia/Ukraine War’, in F. Hopfgartner et al. (eds) Social Informatics. Cham: Springer International Publishing (Lecture Notes in Computer Science), pp. 34–53. Available at: https://doi.org/10.1007/978-3-031-19097-1_3.
South, T., Smart, B., Roughan, M., Mitchell, L. (2022) ‘Information flow estimation: A study of news on Twitter’, Online Social Networks and Media, 31, p. 100231. Available at: https://doi.org/10.1016/j.osnem.2022.100231.
Co-contributor. (2021) ‘Youth National Security Strategy’. Youth National Security Strategy. Available at: https://strategy.ynss.org/credits.
I have held teaching roles for courses ranging from first-year undergraduate to first-year postgraduate. These include:
- Teaching Assistant for Asset Pricing (Hilary Term 2024), Oxford University
- Teaching Assistant for Optimisation for Data Science (Hilary Term 2024), Oxford University
- Teaching Assistant and Tutor for Information Theory (Michaelmas Term 2023 ; Hilary Term 2024), Oxford University
- Tutor for Statistical Modelling and Inference (Semester 2, 2022), University of Adelaide
- Computer Lab Instructor for Maths for Data Science (Semester 2, 2021; Semester 2, 2022), University of Adelaide
- Tutor for Advanced Mathematical Perspectives (Semester 1, 2021; Semester 1, 2022; Trimester 1 2023), University of Adelaide
- Tutor for Professional Practice III (Semester 1, 2022; Semester 1, 2023), University of Adelaide
- Tutor in First Year Maths Help Center and Data Science Help Clinic (Semester 2, 2021), University of Adelaide
113th Rhodes Scholar For South Australia
Westpac Future Leaders Scholarship (2021)
The University of Adelaide Research Scholarship (2021)
Dean’s Commendation for Master by Research Thesis Excellence (2023)
RB Potts Prize for top student in Applied Mathematics Courses (2020)
Shortlisted for best paper award at SocInfo 2022
Best Presentation Award AMSI Connect 2021
Complex systems are present all around us. In these systems, many factors interact, producing complex dynamics and effects. In my research, I'm interested in building robust tools to model this complexity, using mathematical frameworks to understand fundamental drivers and improve our understanding of the world. I bring tools from information science, network science and statistics together to model, characterise and assess uncertainty in complex real-world systems.
My research is supervised by Professor Renaud Lambiotte and Professor Doyne Farmer. I am also working with the Institute of New Economic Thinking Oxford (INET) to apply the methods and insights from my research to real-world datasets. These include the adoption of renewable energy technologies, labour markets, and patent filing rates, to identify areas of rapid innovation and growth.
Keywords: network science, information theory, computational social science, human dynamics, complexity, uncertainty