Hello, I'm
Senior Research Data Engineer
I build reliable research software and data pipelines that help researchers turn messy data into clear answers.
I'm a physicist turned research data engineer, embedded with research teams across disciplines at the University of Sheffield. I design research software, build data pipelines, and steward data through its whole lifecycle — from sensitive NHS health records to environmental sensor streams and genomic sequencing data. I care about FAIR principles, reproducible workflows, and about using AI and machine learning responsibly in the service of good research and scientific discovery.
Before research computing I completed a PhD in physics (atom interferometry) and worked in analytics and software development across financial services. These days I mentor engineers, lead research data projects, and play an active part in the Research Software Engineering community — teaching, writing documentation, and contributing to open source.
University of Sheffield — IT Services
Embedded with research teams across disciplines, designing research software and building data pipelines. Lead engineer on the CUREd+ research database, linking NHS hospital, mental health and ambulance service records to reveal how patients move through the healthcare system. Mentor engineers and contribute to the Research Software Engineering community.
Financial Services
Delivered data analytics and software in the financial services industry, before moving into research computing.
University of Liverpool
Doctoral research in atom interferometry, as part of precision gravimetry and searches for dark contents of the vacuum.
The University of Manchester
Software engineering and data analytics for SORT Online, a platform built with NHS England that lets healthcare organisations self-assess their research readiness — digitising a validated instrument with secure data handling, consent pathways, and dashboards for tracking progress over time.
Case studyA training course teaching researchers how to document their software, developed with the University of Sheffield's Research Software Engineering team.
View courseRe-architected a Computer Science music-generation web app for scalability and maintainability: a decoupled Svelte frontend over a Django REST Framework API, with a Celery task queue and worker processes running the machine-learning jobs asynchronously so the interface stays responsive.
Case studyData engineering for the University of Sheffield's citywide sensor network — robust servers to receive field data-logger signals, bespoke interfaces to bring new sensors online, and Python pipelines ingesting public air-quality and river-level data into research-ready feeds.
GitHubData engineering for the EPSRC-funded AIRBODS project studying building ventilation and airborne SARS-CoV-2 transmission — reliably ingesting IoT air-sensor time-series into secure, well-organised storage that campus and external researchers can query, orchestrated with Apache Airflow.
Case studyA linked healthcare research database bringing together NHS hospital, mental health and ambulance service records, opening new insight into how patients move through the healthcare system.
Case studySoftware-engineering support for the University of Sheffield's COVID-19 Genomics UK (COG-UK) effort: software architecture, containerisation, and automated testing for a Nanopore sequencing pipeline — including a mock sequencing device to accelerate development — helping sequence over 1,000 SARS-CoV-2 genomes.
Case studyI'm especially interested in how agentic artificial intelligence can boost research — used responsibly, in service of better science rather than as a novelty. Alongside my day-to-day work I help organise and take part in the University of Sheffield's wider AI community:
Helping organise the Centre for Machine Intelligence's annual conference for researchers across all disciplines, leading the Programme — arranging talks and hands-on workshops.
Contributing to this Research Data Alliance working group, developing an open blueprint for agentic AI tools that help researchers manage data according to FAIR principles.
Organised a workshop bringing together researchers and support staff to explore practical AI tools and approaches for research support.
Fortnightly reading group exploring agentic AI tools and research. We explore the latest research papers, discuss practical applications, and share insights on how agentic AI can be responsibly integrated into research workflows. We have run sessions on secure runtimes for autonomous agents, hypothesis generation, inter-agent communication protocols, and more.
Regular attendee of Sheffield's AI community meetings, connecting with researchers applying AI across healthcare, education, manufacturing and more.
Have a role, a project, or an idea you'd like to talk through? I'd love to hear from you.