Contact Nathan Cunningham

Background

I am an industry-embedded doctoral researcher working at the forefront of digital engineering, interoperability, and AI-enabled data systems. My research tackles one of the most critical challenges in modern engineering: how complex, data-intensive organisations responsible for complex engineering and infrastructure n can move from fragmented integration to true interoperability-by-design.

I focus on using ontologies, knowledge graphs, and machine-readable semantics to create trusted, decision-ready digital ecosystems in which data flows seamlessly across the design, manufacturing, and operational lifecycles. The goal is not just integration, but meaningful alignment of data, models, and systems to enable faster, better-informed decisions at scale.

Delivered in collaboration with Cranfield University and BAE Systems, my work combines academic depth with real-world industrial application, ensuring that new methods are both theoretically sound and operationally viable.

This research builds on a career leading national research infrastructure, Trusted Research Environments, and globally scaled platforms. It reflects a deliberate shift toward applied, impact-driven innovation, developing reusable AI approaches.

Research opportunities

I am exploring how ontology-driven digital engineering can transform the way complex systems are designed, integrated, and operated. My research sits at the intersection of data, systems engineering, and AI, with a focus on solving one of the hardest problems in modern engineering: interoperability at scale.

I am particularly interested in how knowledge graphs, semantic technologies (RDF, OWL, SHACL), and FAIR data principles can be applied to create decision-ready digital ecosystems—where data from across design, manufacturing, and operational lifecycles can be seamlessly connected and trusted.

Building on a career delivering national-scale data platforms, Trusted Research Environments, and AI-ready infrastructure, I am now focused on developing:

- Ontology-led frameworks for integrating heterogeneous engineering data

- Federated digital twin architectures that enable system-of-systems insight

- Validation and governance approaches that ensure data quality, provenance, and trust

- AI-enabled reasoning systems that turn complex data into actionable decisions

My work is grounded in real-world industrial challenges, particularly through collaboration with BAE Systems, aiming to bridge the gap among model-based engineering, data platforms, and operational decision-making.

Publications

Articles In Journals

Books