Profile
MPhys graduate specialising in observational cosmology, statistical methods and astrophysical theory.
My research focuses primarily on Type Ia supernova standardisation for improved cosmology, with broader interests in astrophysics, statistical inference, general relativity, cosmological inflation and theoretical models of the Universe.
Research Experience
Principal Component Analysis of Type Ia Supernova Spectra
MPhys Research Project
Investigating whether principal component analysis can improve Type Ia supernova standardisation by incorporating spectral information beyond SALT2. The project explores spectral reconstruction, dimensionality reduction, twinning and improved cosmological distance estimation.
View Research Collection →Dark Energy Parameter Optimisation
Third Year Group Project
Preliminary investigation into optimising dark energy equation of state parameters using mock Euclid observations and statistical fitting techniques.
Research Outputs
Research Report
MPhys Dissertation
Principal Component Analysis of Type Ia Supernova Spectra: Improving Standardisation and Twinning
View PDF →
Review
Literature Review
Evaluation of Spectral Techniques in Type Ia Supernova Standardisation for Cosmology
View PDF →
Poster
PLACE Conference Poster
Principal component analysis of Type Ia supernova spectra for improved standardisation
View PDF →
Education
Lancaster University
2022–2026
MPhys Physics, Astrophysics & Cosmology
First Class
Cockermouth School
A Level Results
GCSE Results
Art, Biology, Design Technology, Mathematics, Physics
9
Chemistry
8
English Literature, English Language, French, Geography
7
English Spoken Language
Distinction
Academic Highlights
Special Relativity Examination
PHYS232
93.3%
Statistical Data Analysis in Physics
Master's Level (MPhys Year 4)
86.9%
Mathematics II
85.2%
Scientific Programming & Modelling
80.7%
Awards & Recognition
PLACE Research Conference
Presentation & scientific communication
A
MPhys Research Logbook
Independent research progress and record keeping
A/A+
MPhys Project Report
PCA of Type Ia supernova spectra
A−/A
Technical Expertise
Programming
Python
TypeScript
Next.js
Git
Analysis
PCA
Regression
Statistical inference
Machine learning
Scientific Tools
NumPy
Pandas
Scikit-learn
Matplotlib
Links