# Alina Isobel Hagan

> Software Engineer | Darktrace | Rust/C++ | High-Performance Systems | Cybersecurity | PhD Particle Physics | Maker

Location: London, England, United Kingdom
Profile: https://flows.cv/alinaisobelhagan

Software engineer specialising in high-performance systems, with a background in particle physics and experience building efficient, reliable software in cybersecurity environments. My research background in particle physics trained me to work on computationally intensive, data-heavy systems—skills I now apply to building performant and secure software.

## Work Experience
### Software Engineer @ Darktrace
Jan 2025 – Present | London Area, United Kingdom
Lead contributor on a high-impact project. Individually authored multiple services by handling a diverse and growing tech stack in a network detection and response context. Delivering tooling centred around customer and partner needs by focussing on high-quality code output and coordinating testing and further development across multiple teams.

### Analysis Lead @ ATLAS Collaboration
Jan 2020 – Jan 2024 | Meyrin
Spearheaded the coordination and evolution of a novel analysis at the LHC. Oversaw live data collection and coordinated with a large team of international experts, ensured robust data integrity and system performance. Delivered informative insights into the internal structure of the proton.

### Doctoral Student @ Lancaster University
Jan 2020 – Jan 2024
Completed a pioneering 4-year analysis on proton structure, demonstrating strong analytical and problem-solving skills. Highly competent in applying advanced statistical methods, data modelling and performant programming design principles to evolving problems.

### Experimental Particle Physics Intern @ University of Glasgow
Jan 2020 – Jan 2020 | Glasgow
Modern analysis of CERN and LHC data, pushed forward the development of novel physics-informed methods for data purification and managed the development of systematic error analysis.

### Nuclear and Hadron Physics Research Group Intern @ University of Glasgow
Jan 2019 – Jan 2019 | Glasgow
Design of cutting-edge Graph Neural Networks for clustering. Developed pipeline for training and testing experimental model networks.


## Education
### Doctor of Philosophy - PhD in High Energy Particle Physics
Lancaster University

### Master of Science - MS in Physics
University of Glasgow


## Contact & Social
- LinkedIn: https://linkedin.com/in/alina-isobel-hagan-3a62a6255
- Website: https://aihphysics.github.io

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Source: https://flows.cv/alinaisobelhagan
JSON Resume: https://flows.cv/alinaisobelhagan/resume.json
Last updated: 2026-04-05