Research
From the cosmic web to galaxies to cancer cells
I am a cosmologist working at the intersection of theory and observation. My research spans the largest scales of the Universe down to the scales of galaxies, using simulations, gravitational lensing and galaxy surveys to uncover what the cosmos is really made of and to test whether our picture of gravity and dark energy still holds. I also develop Bayesian statistical tools which are applied both in cosmology and in cancer research.
Weak gravitational lensing
The subtle, coherent distortion of billions of galaxy shapes by intervening mass: a direct probe of the dark matter between us and them.
Strong gravitational lensing
Arcs and multiple images where gravity bends light most sharply, weighing dark matter and structure on the scales of individual galaxies.
Large-scale structure & galaxy clustering
Modelling the galaxy-traced cosmic web: the filaments, walls and voids whose growth over cosmic time encodes dark matter and dark energy.
Forward simulations
Building synthetic universes that connect theoretical models with what surveys such as Euclid and KiDS actually see.
Bayesian & simulation-based inference
Developing rigorous, simulation-based inference pipelines that extract dark-matter and dark-energy constraints from real data.
Applications to cancer research
Applying Bayesian inference techniques from astrophysics and cosmology to tools for personalised cancer treatments.