My research principally focuses on machine/deep learning techniques for time-domain astrophysics, as well as high-cadence observations of transients, Bayesian methods, and general astronomical software development – with a particular focus on applying state-of-the-art computational techniques from the ML literature to hard problems/datasets in astrophysics.
I am a keen advocate for open-source development, and reproducible workflows in astronomy and astrophysics. I primarily code in Python, and use a combination of TensorFlow and JAX for my ML work.
I am always keen to start new collaborations and projects on topics of interest - please get in touch!
PhD student University of Warwick