I completed my undergraduate studies at UCL, receiving an MSci in Astrophysics in 2021. My 3rd year group project focused on exoplanets, specifically transit timing variations in the orbits of "Hot Jupiters", while my MSci dissertation was on instrumentation and data analysis. I also completed an RAS Summer Internship at MSSL, using recurrent neural networks to predict risks to infrastructure from space weather. 

In my research, I am combining these interests of exoplanets and state-of-the-art data science techniques. This is because while the wealth of new data from recent space missions such as Gaia, Kepler and the Transiting Exoplanet Survey Satellite (TESS) presents an opportunity to uncover new insights about the exoplanet population, the volume and complexity of the data can make it challenging to fully analyse and understand. As well as developing Machine Learning, Bayesian and Monte Carlo techniques to discover and classify exoplanets and their host stars, I look forward to employing my skills in non-academic contexts through the CDT industrial placements. 

Outside of my research, I am a strong advocate of science outreach: I run public tours at UCL Observatory, I teach coding to school students from disadvantaged and under-represented backgrounds, and I have worked as a teaching assistant in undergraduate observatory practical courses.