Saleh Masum

Saleh's research investigates how agentic AI can transform fragmented digital health data into actionable, personalised, and explainable wellness intelligence. Today, individuals generate health-relevant data from a growing array of devices and applications — wearables, home sensors, sleep trackers, nutrition apps, and more — yet this data remains siloed and rarely translates into meaningful, actionable guidance.

The project proposes an agentic, modular orchestration framework that autonomously integrates data from these diverse sources to support proactive and continuous wellness management. Unlike static recommendation systems, the framework is designed to reason dynamically about an individual's context, adapting its outputs as circumstances change over time.

Two qualities are central to the research vision: trustworthiness and explainability. 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 the burden of chronic illness, and improves the efficiency of healthcare ecosystems. The involvement of industry partner Future Wellness Group grounds the work in real-world deployment constraints and user needs.