Samuel Jackson
Data Scientist | Research Software Engineer
👋 Hi! I’m a data scientist working in the machine learning and visualization group at the UK Atomic Energy Authority.
I’m interested in applying machine learning and data science techniques to solve problems in the physical sciences. My current work focuses on understanding and exploiting historical diagnostic data from tokamak devices operated by UKAEA (MAST, MAST-U, and JET), as well as how we can improve data curation, management, and access to these important datasets.
I am an advocate for open data, open source software, FAIR data principles, and reproducible research. I have a computer science background with expertise in machine learning, data science, software engineering, and HPC systems. I mostly work in Python, but I also have experience with C++, Typescript, and a few other languages.
news
| Mar 24, 2026 | New co-authored JOSS paper: DisruptionPy: An open-source physics-based scientific framework for disruption analysis of fusion plasmas |
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| Mar 10, 2026 | Released new open source software package: TokTagger for interactive tagging of tokamak diagnostic data, which was presented by a colleague at OSSFE. |
| Feb 16, 2026 | New co-authored arxiv submissions: TokaMark: A Comprehensive Benchmark for MAST Tokamak Plasma Models and TokaMind: A Multi-Modal Transformer Foundation Model for Tokamak Plasma Dynamics |
| Sep 24, 2025 | Attended AAPPS-DPP conference and delivered a talk on Towards Open Machine Learning Datasets with AI Driven Annotation |
| Aug 18, 2025 | New paper published: An open data service for supporting research in machine learning on tokamak data |