AI&IoT研讨会 | Learning Health State and Disease Risks from…

🎤 Speaker

Dr. Hang Yuan

NDPH Early Career Research Fellow at the University of Oxford

📰 Title

Learning Health State and Disease Risks from Human Movement

⏰ Time

14:30 -15:30, Beijing Time

📅 Date

6 May 2026, Wed

Human Movement is a key determinant of health. Activities of daily living such as number of steps we take and the amount of sleep we get have are closely linked to both physical health and mental well-being.

The increasing availability of high-frequency, longitudinal data from wearable devices presents a unique opportunity to quantify these behaviours at scale and study their cause-effect associations on health outcomes.

We will dive into the historical accounts of behavioural health research, and how modern AI methods could learn what it means to be healthy for a future of medicine that is preventive, precise and personalised.

Dr. Hang Yuan

NDPH Early Career Research Fellow 

at the University of Oxford

Dr. Hang Yuan is currently an NDPH Early Career Research Fellow at the University of Oxford, with a focus on developing general-purpose foundational machine learning methods for wearable sensors to improve human health at scale. He published in leading journals and machine learning conferences including npj Digital Medicine, Lancet Longevity, Lancet Rheumatology, and Nature Communications. His research has been adopted by international pharmaceutical companies in digital health efforts such as GSK, Roche, and Novo Nordisk, contributing to approximately £700K in research funding to date.