PhD student in statistics - interested in statistical modeling of network data.
In partnership with Elsevier, a global information and analytics business, this project explores approaches to statistical analysis of their often high-dimensional but structured datasets.
By applying and developing tools from network analysis to usage data for their platforms, we look to uncover features that will aid Elsevier in understanding how their products are being used, thus guiding their future development and improving the user experience.Find out more
The STOR-i Centre for Doctoral Training (CDT) is an EPSRC funded joint venture between the departments of Mathematics and Statistics and Management Science at Lancaster University. The centre offers a pioneering four-year PhD programme in Statistics and Operational Research (STOR), developed and delivered with various industrial partners. I am currently in the first year of my PhD, along with twelve other students. Including those in the earlier and later years of the programme, there is a total of around fifty students at the centre, working on a diverse range of research projects. If you would like to find out more, you can take a look at the video below, or head to the website.
I was born and raised in Herefordshire. I did my undergrad at the University of Manchester, studying for a BSc in mathematics. Whilst there, I studied a variety of topics in pure mathematics and statistics. My interest in the latter grew throughout my three years at Manchester, with my enjoyment of final-year modules in Extreme Value Theory and Time Series Analysis inspiring me to pursue further study in the field.
I moved to Lancaster University in 2018, starting a 4 year MRes+PhD programme at the STOR-i CDT. Over the course of the MRes I developed an interest in network analysis, opting for two network-related topics as research projects: network flow optimisation problems and statistical community detection in social networks. Following completion of the MRes I have begun working on my PhD project in partnership with Elsevier, where we are looking to develop statistical network modeling methodologies applicable to clickstream data.