Research & Applied Work
A selection of research, teaching, and applied analytics projects — focused on solving real problems with principled statistical methods and modern AI tools.
Featured Research
MSc Masters Project · Distinction
Assessed and characterised the ability of Large Language Models (LLMs) to solve sequential decision-making problems, with a focus on the Multi-Armed Bandit (MAB) problem. The research evaluated whether modern LLMs can replicate, complement, or exceed classical decision strategies and explored their fundamental capabilities and limitations in sequential reasoning under uncertainty.
Supervisor: Prof Audrey Durand — Université Laval, Canada.
★ Awarded DistinctionDeveloping novel statistical methods for modelling longitudinal dietary patterns and their association with health outcomes. Funded by the Research Ireland Frontiers for the Future Programme. Supervised by Assistant Professor Silvia D'Angelo.
Evaluating how Large Language Models perform on multi-armed bandit style tasks and where they can complement classical methods. Awarded Distinction. Supervised by Prof Audrey Durand (Université Laval, Canada).
Studied key relay protocols for quantum key distribution through the prestigious g-RIPS-Sendai collaborative programme — a joint initiative of IPAM (UCLA), AIMR, and Tohoku University, Japan.
Programme details →Hands-on material for statistics students covering data wrangling, visualisation, modelling, and reproducible analysis in R and RStudio. Built for undergraduate and postgraduate learners.
View course →Built and validated IFRS 9 credit risk models for financial institution clients — including Probability of Default (PD), Loss Given Default (LGD), Exposure at Default (EAD), and Macroeconomic Variable (MEV) components.
Completed the Africa Scientifique science communication workshop — building skills in clear scientific writing, public engagement, and communicating research to non-specialist audiences.