Used state of the art data-driven sparse model selection techniques combined with data assimilation methods to create an optimisation framework for identifying underlying equations of a physical system from data when not all variables are observed.

MATH 228-2: Multiple Integration and Vector Calculus.Cylindrical and spherical coordinates, double and triple integrals, line and surface integrals. Change of variables in multiple integrals; gradient, divergence, and curl.

Developed the mathematical framework to accurately locate individual nanoparticles using visible light and the theory which describes the interference pattern. Combining theory with simple measurements of the observed pattern we are able to identify the particle location.

In my thesis I developed and analysed mathematical models of the growth or shrinkage of nanoparticles. The initial work built on mathematical models of melting at the nanoscale, and involved solving heat equations coupled to a phase change model, using approximate analytical and numerical methods. The other phenomena which I modelled was the Kirkendall effect with the aim to understand how to create hollow structures at the nanoscale. My training at CRM was funded by "la Caixa" Foundation within the programme Research on Collaborative Mathematics​​.

Visiting International Research Student at the Institute of Applied Mathematics (IAM) as part of my PhD working on the nano-Kirkendall effect.

I worked with the UBU Postgraduate Network to audit and analyse engagement and representation of postgraduate researchers across the University, including communications channels, the processes for recruiting PGR reps, and access to training opportunities.