About us

Putting people at the centre of AI

Artificial intelligence is changing how we understand health, identify risk and deliver care. Technical performance alone is not enough.

Successful AI must be acceptable, equitable and implementable in real health and social care systems.

The HM-AI Group brings together expertise in epidemiology, data science, artificial intelligence, population health, behavioural science, implementation and commercialisation. We work with patients, caregivers, clinicians, policymakers and industry to develop evidence-based innovations for people with multimorbidity that can be scaled and adopted in real-world settings.

Using data and AI to improve health and care for people with multiple long-term conditions.

Mission

Predict. Prevent. Transform.

Using AI to predict disease trajectories, prevent progression and transform care for people with multiple long-term conditions — aiming for internationally recognised leadership in trustworthy, equitable human-centred AI.

Illustration of people and clinicians gathered around a flowing health data ribbon, representing human-centred AI in care

Our people

Meet the team

Our multidisciplinary team brings together expertise in AI, epidemiology, population health, behavioural science, implementation, engineering, commercialisation and lived experience.

Prof. Hajira Dambha-Miller

Group Director

Prof. Dambha-Miller is an internationally recognised leader in artificial intelligence, digital health and population health. Her research focuses on using AI and linked health data to improve the prediction, prevention and management of multiple long-term conditions, while advancing equitable and sustainable health and care systems. As Group Director, she provides the strategic vision for the group and leads multidisciplinary research spanning AI development, digital phenotyping, population health intelligence and health system innovation, with a strong focus on translation through partnerships with the NHS, industry and international collaborators.

Research interests: Artificial intelligence; digital health; population health; multiple long-term conditions; clinical prediction; digital phenotyping; health inequalities; learning health systems.

Dr. Lucy Smith

Group Coordinator and Lead for Human-Centred AI, Co-production & Implementation

Dr. Smith is a human-centred AI researcher whose work focuses on ensuring artificial intelligence is designed, implemented and evaluated in partnership with the people and communities it is intended to serve. Her research bridges AI, behavioural science, implementation science and lived experience to develop technologies that are equitable, trustworthy and capable of delivering meaningful improvements in health and social care. She leads the strategic development and coordination of the group and has particular expertise in co-production, qualitative and mixed-methods research, intervention development, research inclusion and reducing health inequalities.

Research interests: Human-centred AI; co-production and co-design; implementation science; behavioural science; multiple long-term conditions; digital health; health equity and inclusion; public involvement; qualitative and mixed methods.

Dr. Seyi Ayinde

Postdoctoral Research Fellow, Keele University

Dr. Ayinde is a Postdoctoral Research Fellow based at Keele University and a member of the group. His research focuses on applying artificial intelligence, epidemiology and advanced health data analytics to improve understanding of multiple long-term conditions and support more effective and equitable health and care systems. He works with large-scale linked datasets to identify patterns of disease, understand complex trajectories and generate evidence for clinical practice, policy and prevention.

Research interests: Artificial intelligence for health; epidemiology; multiple long-term conditions; population health intelligence; linked health data; clinical prediction; machine learning; health inequalities; prevention.

Mr. Aman Jat

Epidemiologist and Machine Learning Researcher

Aman is an epidemiologist and machine learning researcher whose work combines population health science with advanced analytical methods. He develops and applies machine learning approaches to identify disease trajectories, predict health outcomes and understand the interactions between multiple long-term conditions. His work supports earlier intervention, personalised prevention and evidence-informed health and social care.

Research interests: Epidemiology; machine learning; artificial intelligence for health; multiple long-term conditions; population health intelligence; disease trajectory modelling; linked health data; risk stratification; prevention.

Mr. Yousef Yousef

Commercialisation Fellow

Yousef is a Commercialisation Fellow specialising in engineering, digital innovation and the translation of research into real-world health and social care solutions. He works across multidisciplinary teams to support the design, development, evaluation and commercialisation of AI-enabled technologies. Within the group, he strengthens industry collaboration, product development, implementation pathways and routes to adoption at scale.

Research interests: Engineering; AI-enabled digital health; medical technology development; commercialisation; product development; health technology evaluation; industry partnerships; adoption and scale-up; human-centred design.