I am a PhD student in astrophysics, working with Greg Ashton and Nicolo Colombo on using machine learning for gravitational wave analysis. I am currently working on applying conformal prediction to determine uncertainties. When making use of machine learning, for example applied to gravitational wave parameter estimation, quantifying the uncertainty of how accurate the estimate is is essential. Conformal prediction provides a method to determine this uncertainty for any point prediction algorithm.

My background is in theoretical physics and astrophysics, with a Masters degree from the University of Glasgow. In my masters project, working with John Veitch, I applied machine learning in the form of normalising flows to model and hence remove glitches from gravitational wave data, with the aim to improve the Bayesian inference based parameter estimation in the presence of glitches.

Besides research, I enjoy volunteering with projects promoting science and engaging young people in STEM, and have been involved in various projects with the Swedish Federation of Young Scientists, such as organising Rays Research Academy for Young Scientists. In my free time I also enjoy a variety of outdoor activities as well as good literature.