Agentic AI Architect for Predictive Systems, Data Platforms & Governance

I specialise in the design and deployment of advanced artificial intelligence systems for complex data environments, with a focus on agentic AI architectures, large language models (LLMs), retrieval-augmented generation (RAG), and predictive modelling.

My work focuses on integrating heterogeneous data streams such as sensor data, biomedical information, behavioural signals, and environmental data into scalable AI platforms capable of reasoning, prediction, and adaptive decision support.

I develop AI systems that combine:

• agentic AI with coordinated specialised agents
• LLMs and retrieval-augmented knowledge systems
• predictive modelling and anomaly detection
• knowledge graphs and semantic interoperability (FAIR data principles)
• federated and privacy-preserving learning
• digital twins for modelling complex systems
• sensor analytics and distributed data infrastructures

A key component of my work is the governance of AI systems, including frameworks that support transparency, explainability, accountability, and compliance with emerging regulatory frameworks such as the EU AI Act.

Within collaborative R&D projects I contribute to AI system architecture, agent orchestration, data integration, predictive modelling, and the development of trustworthy AI decision-support platforms.

I also serve as an Independent Expert Evaluator for the European Commission (EIC Accelerator), assessing deep-tech innovation, technology readiness levels (TRLs), and commercial feasibility.

Recent work includes AI platforms for preventive health intelligence, personalised nutrition, and physiological modelling.

Typical role in collaborative R&D projects:

• AI architecture and system design
• development of predictive modelling pipelines
• integration of heterogeneous data platforms
• implementation of agentic AI systems
• governance frameworks for trustworthy AI