Harry Birch

I am student part of Cohort 1 of the NUdata CDT, a joint collaboration between Newcastle and Northumbria Universities. My research interests inlclude the application of machine learning (ML), in particular deep learning, to solar physics problems. My current research involves a computer vision scenario of prominence detection and classification, using object detection convolutional neural networks (CNNs). I am also working on combinig machine learning with other techniques to uncover prominence physics, such as their structure, morphology, and evolution.

I am currently working with the Met Office on CME forecasting and prediction using real time data and machine learning. This project is in collaboration with GeoSphere Austria and focuses on using in-situ data from WIND and DSCOVER to train ML models to predict if a CME has arrrived.

I completed my MPhys (4 year combined bachelors and masters) degree at the University of Leeds 2020, focusing on biophysics and modelling of protein/ligand interactions.

After two years in industry working as a machine data analyst for an enginerring company, I returned to academia, as part of the fist cohort of the NUdata CDT program, working in the Solar and Space Physics research group at Northumbria University. I am currently on a placement at the Met Office, working on the CME forecasting.

Outside of my studies, I am a keen pianist (having been playing for over 20 years!) and regular badminton player.

Email: [email protected]