Mei Lan Fang

Assistant Professor

Gerontology & Urban Studies

Mei Lan Fang

Assistant Professor

Gerontology & Urban Studies

Dr. Mei Lan Fang is an Assistant Professor specializing in Urban Aging within the Urban Studies program and the Department of Gerontology at Simon Fraser University, Canada. She also serves as the Undergraduate Chair for the newly launched BA in Urban Worlds program. In addition, Dr. Fang is a Visiting Scholar at the School of Health Sciences, University of Dundee, Scotland.

For the past decade, Dr. Fang has led and contributed to ageing in place and wellbeing research to inform the development of age-friendly cities and communities as a Community-Engaged Research Scientist and Qualitative Health Research Methodologist. Her research involves interrelated areas of ageing well in place (environmental gerontology), inclusive digital place-making (ageing and technology) and critical public health (social inequities and health). Dr. Fang’s research approach is transdisciplinary, participatory, community-focused and qualitative through applying narrative and visual co-creation methods, and integrated knowledge translation techniques including: autobiographical and digital storytelling, story mapping, community mapping, photo-voice and photo-tours, community walk-along interviews, deliberative dialogue, and knowledge cafés.

Dr. Fang’s current research is informed by the sustainable development goals (SDGs) 3, “ensure healthy lives, promote wellbeing for all at all ages,” and 11 “make cities and human settlements inclusive, safe, resilient and sustainable”. An important area of her research surrounds the development of Intergenerational and Age-Friendly Living Ecosystems, an idea that has translated into a large scale ESRC funded (£1.7 million) multi-site project, where Dr. Fang’s involvement as Co-Principal Investigator, is to explore and understand inclusive and exclusionary physical places and virtual spaces with older people with intellectual and developmental disabilities and older people who identify as LGBTQ+ using ArcGIS Story-mapping and Social Network Analysis.