Fiona Walter

Professor Fiona Walter is Director of the Wolfson Institute of Population Health at Queen Mary University of London, within the Faculty of Medicine and Dentistry. She previously held the role of Reader in Primary Care Cancer Research at the University of Cambridge and has worked as an NHS General Practitioner for over 30 years. Her research focuses on developing and evaluating diagnostic tools for early cancer detection in primary care, including leadership roles in the CanTest Collaborative and NIHR Policy Research Unit in Cancer Awareness. She co-leads an NIHR Global Research Group advancing early cancer diagnosis in Southern Africa and holds an honorary academic role at the University of Melbourne. Key initiatives include the CanTest International School for Cancer Detection Research and work on AI-driven skin cancer diagnosis. Her expertise spans global health equity, diagnostic pathway optimization, and implementation science in oncology.

Education & Professional Background:

• Professor in Primary Care Cancer Research, Queen Mary University of London (2021–present)
• Reader in Primary Care Cancer Research, University of Cambridge (prior to 2021)

Research Interests: Fiona’s work integrates clinical practice with translational research, emphasizing:

• Primary care-based early cancer detection strategies
• Health technology implementation (e.g., AI in diagnostics)
• Global health equity in cancer care
• Multifactorial risk assessment models
• Policy-driven cancer awareness initiatives

Her projects bridge clinical practice, policy, and global health disparities.

Grants & Collaborations: Lead roles in Cancer Research UK’s Catalyst Award, NIHR Policy Research Unit, and global partnerships with institutions in Southern Africa and Australia. Active in multi-disciplinary networks including the Spatial Biology Hub and CanTest Collaborative.

Future Work: Expanding AI-driven diagnostic tools in resource-limited settings, optimizing cancer risk communication, and addressing disparities in early diagnosis outcomes across ethnic and geographic populations.