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Andrew Low: Observations of a Senior Fullstack Engineer
in the Solar Physics Regime

A. Low1

1Durham University  ·  contact@ackl.me  ·  andrew.low@durham.ac.uk

Abstract We present a longitudinal study (2014–present) of a fullstack engineer with ten years of experience delivering high-scale e-commerce platforms and data-driven interfaces for clients including Mulberry, Gucci, and Moët Hennessy. Recent observations show a strong migration toward scientific computing: the subject is completing an MSc at Durham University, applying physics-informed neural networks to the extrapolation of nonlinear force-free magnetic fields in the solar corona. The subject remains stable in production.

1Work

Ten years of senior fullstack engineering - React/TypeScript, Python, payments, performance, and platform architecture - most recently at Grid Dynamics (2021–2024).

MSc Scientific Computing & Data Analysis (Astrophysics), Durham University. Dissertation: Physics-informed neural network based extrapolations of nonlinear force-free magnetic fields in the Solar corona.

Previously BSc Astrophysics (First Class Honours), Queen Mary University of London. Dissertation: Magnetic fields in the solar corona

2Selected Artefacts

3Data Availability

† The author acknowledges support from strong coffee and the London Underground. Conflicts of interest: the author both loves and hates technology. This page was typeset by hand.