Agentic AI-Driven Modular Orchestration for Trustworthy Predictive and Personalized Wellness

Agentic AI-Driven Modular Orchestration for Trustworthy Predictive and Personalized Wellness

This PhD research investigates how agentic AI can be used to transform fragmented digital health data into actionable, personalised, and explainable wellness intelligence. The project proposes an agentic, modular orchestration framework that autonomously integrates data from wearables, home sensors, and mobile health applications to support proactive and continuous wellness management. By leveraging autonomous coordination, contextual reasoning, and explainable decision-making, the research aims to enable ethically aligned, human-centred health intelligence that supports lifelong self-management, reduces chronic illness, and improves the efficiency of healthcare ecosystems.

Project Lead

Saleh Masum

Project Team

Prof John Grundy, Chetan Arora, Mark Foley