Welcome to my website!

Bio

I am an applied mathematician developing methods to help model Earth systems. I am currently a postdoc working with Aretha Teckentrup at the University of Edinburgh. Before that I was a PhD student in the MAC-MIGS centre for doctoral training. My thesis 'Stochastic modelling and inference of ocean transport' was supervised by Jacques Vanneste. Before that I studied for a BSc in Applied Mathematics from the University of Edinburgh.

Research interests

My interests are at the intersection of dynamics and uncertainty. Some specific topics are:

– Stochastic parameterisation of sub-grid-scale turbulence

– Stochastic modelling of Lagrangian particles

– Probabilistic machine learning

Publications

– Brolly, M. T. (2025). Stochastic parameterization: The importance of nonlocality and memory. Journal of Advances in Modeling Earth Sytems, 17, e2025MS005223. doi. arXiv.

– Brolly, M. T. (2023). Inferring ocean transport statistics with probabilistic neural networks. Journal of Advances in Modeling Earth Sytems, 15, e2023MS003718. doi. arXiv.

– Brolly, M. T., Maddison, J. R., Teckentrup, A. L., & Vanneste, J. (2022). Bayesian comparison of stochastic models of dispersion. Journal of Fluid Mechanics, 944, A2. doi. arXiv.

Thesis

– Brolly, M. T. (2023). Stochastic modelling and inference of ocean transport. The University of Edinburgh. doi.

Updates

• We are hosting a Workshop on Uncertainty Quantification for Dynamical Modelling in Edinburgh, 9-11th July. See the workshop page for details.