Artificial Intelligence & Data Science
Machine learning, explainable AI, predictive analytics and intelligent decision-support systems designed for real-world validation and responsible deployment.
Long-term agenda
A coherent research identity connecting AI, cyber security, digital health and intelligent infrastructure.
To develop trustworthy artificial intelligence and secure digital technologies that improve healthcare, strengthen cyber resilience, optimise critical infrastructure and support evidence-based decision-making through interdisciplinary collaboration and real-world translation.
My long-term research agenda connects artificial intelligence, cyber security, digital health and intelligent infrastructure into one coherent programme of work. Rather than treating these as separate silos, I focus on systems that are clinically and operationally meaningful, security-aware by design, and capable of generating evidence for adoption.
In digital health and rehabilitation, this means platforms such as RehabSense, RehabNexus and ReferIQ that support monitoring, integration, referral workflows and human-supervised decision support. In cyber security and trustworthy systems, it means embedding privacy, oversight and secure architecture into AI-enabled services. In smart infrastructure, it means translating forecasting and optimisation into practical tools such as FlexGrid AI.
The goal is research impact: prototypes that demonstrate technical leadership, publications and partnerships that build evidence, and pathways toward deployment with universities, NHS partners, funders and industry collaborators.
Machine learning, explainable AI, predictive analytics and intelligent decision-support systems designed for real-world validation and responsible deployment.
Cryptographic engineering, secure communications, secure system design and trustworthy computing — alongside security-relevant machine learning, privacy-aware design and cyber considerations for healthcare and cloud environments.
Clinically informed platforms for rehabilitation monitoring, technology integration, referral intelligence and health AI — with emphasis on interoperability, human oversight and translational impact.
AI-enabled optimisation, analytics and coordination for energy and infrastructure contexts, building on control, distributed systems and data-driven modelling.