CV

MSci Physics

Imperial College London

Physics

PhD in Physics

University of Cambridge

Physics (Cosmology)

• Machine-learning-enhanced Bayesian inference on cosmological projects
• Main author of unimpeded, an open-source Python package for parameter estimation, model comparison and tension quantification
• Contributing author of anesthetic, a Python package for processing nested sampling chains
• Developing machine-learning-accelerated nested sampling methods
• Studying star formation in galactic outflows via astronomical spectroscopy

Master's Project: Investigating Anomalies in the Cosmic Microwave Background Sky

Built Python algorithm to evaluate unusual features in the CMB using Bayesian statistics with 150,000 simulated universe temperature maps. Supervisor: Professor Alan Heavens

• Python
• Bayesian statistics
• Big data analysis

Bachelor's Project: The Map of the Universe

Developed Python algorithm to calculate future trajectory of stars and planets in geocentric coordinate system. Supervisor: Professor Roberto Trotta

• Python
• Differential geometry
• Animation

Undergraduate Summer Research Intern

University of Cambridge

12-week research internship in the Cavendish Astrophysics Group

• Evaluated calibration strategy for radio antenna