My PhD is focused on measuring the intrinsic alignment of galaxies, which is a source of potential contamination to measurements of weak gravitational lensing, but also itself an interesting tracer of galaxy evolution and cosmology. I am an active member of the Dark Energy Science Collaboration. I am also actively researching the use of machine learning methods to accelerate the inference of cosmological parameters from data.
Previously, I have also worked on developing a system to monitor transitional millisecond pulsars. My current and past research has given me experience working with large observational datasets from the Dark Energy Survey and Fermi-LAT, and I hope to have the opportunity to work with Rubin Observatory data in the near future when it is available.

Outside my research, I am passionate about science communication to the general public and computing technologies, ranging from hardware and chip architecture to software and AI. My hobbies include cooking, fitness, and music.