Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

PHI group graphic

Welcome to the Planetary Health Informatics Group. We use artificial intelligence and remote monitoring technology with international real-world health and environment data, in order to further our understanding of disease and fills the gaps in global health, leveraging common data models and federated network analytics.

We work closely with clinicians, engineers, epidemiologists, conservationists, data scientists, and public and patient groups in the UK, Europe, Latin America, South Asia, and Africa to co-create models for equitable and ethical solutions for planetary health problems. 


  1. Artificial intelligence for equitable and ethical healthcare
  2. Digital platforms and open-science tools for linked health, environment, and climate
  3. Health data science via common data models (OMOP), federated distributed analytics (FDN), and trusted research environments (TRE)

We teach a number of health data science courses at NDORMS and University-wide including but not limited to the NDORMS/MSD DPhil module on "Observational health data science: epidemiology, machine learning, and health economics", the NIHR BRC training course on “Data analysis: statistics - designing clinical research and biostatistics", and as faculty members, the "Real World Evidence using the OMOP Common Data Model" summer school.

Latest news

New advanced analytics research to deliver next level of insights into COVID-19

NDORMS is leading one of nine new studies awarded total of £2m to use large-scale linked data to address priority research questions that will improve understanding of the pandemic and inform the continued policy response.

social media feed