Dr Emmanuel Olamijuwon

Dr Emmanuel Olamijuwon

Lecturer

Researcher profile

Phone
+44 (0)1334 46 2484
Email
e.olamijuwon@st-andrews.ac.uk

 

Biography

I am a Lecturer (Assistant Professor) in Social and Health Data Science/Literacy with a teaching and research portfolio at the intersection of digitisation, health, and inequality. I joined the University in 2021 as a Research Fellow on the CARE project, having previously worked in Eswatini for five years. I then joined the University of Southampton as a CHERISH Research Fellow before returning to St Andrews in 2023.

As the school’s employability officer, I also support students' career development by organising events, such as GreenCareers Day, and creating opportunities to engage with alumni, employers, and showcase their work.

Through initiatives such as the Summer Institutes in Computational Social Sciences, which I have co-led in Nigeria, Ghana, and South Africa, I have directly supported over 100 early-career African researchers in developing advanced data science skills. Many participants of these programmes now lead similar initiatives in their respective institutions and countries across Africa.

Teaching

My teaching reflects and extends my research interests by focusing on the critical intersections of digitisation, health, and inequality. I aim to equip students with both theoretical understanding and practical skills in data literacy, enabling them to tackle real-world social and health challenges. As a Lecturer in Social and Health Data Science/Literacy, I contribute to the following modules:

  • SD4129: Digital inequalities and sustainable development: Trends, patterns, and implications
  • SD5034: Health, Inequality and Development
  • SD5810: Welcome to Data: Rubbish In; Rubbish Out
  • SD5811: Statistical Foundations
  • SD5812: Quantitative Methods
  • SD5813: Advanced Data Visualisation

Research areas

I am interested in the intersection of digitisation, social inequality, and population health, with a regional focus on sub-Saharan Africa. My research applies computational social science approaches and machine learning to address key social and global health topics, such as immune correlates of protection and union formation, among others.

I integrate quantitative and qualitative methods, drawing on diverse data sources including social surveys, digital traces, medical records, and crowdsourced data. My work increasingly emphasises methodological innovation and the development of data science tools for global health research.

Over the past five years, my research has contributed to:

  • Developing methods to improve digital surveys and overall survey quality.
  • Applying novel and advanced quantitative/qualitative methods to key social and health issues such as antimicrobial resistance.
  • Developing data-driven tools and applications for public health research and intervention

PhD supervision

  • Victor Emmanuel
  • Winifred Maduko

Selected publications

 

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