Curriculum Vitae

BSc Public Health, Miva Open University

Focus on health information systems, data analysis, public health interventions and community health programmes.

Diploma in Software Engineering, APTECH Abuja

Web development, database management, software engineering and UI/UX design.

Founder & CEO, VitaLink

Healthcare operating system and infrastructure platform for Africa, formerly Switch Health. I lead product and engineering.

SIWES placement, The Leprosy Mission Nigeria

PROSKIN project: leprosy and skin NTD surveillance. Also built DOHRMP, the organisation’s operations platform.

Freelance developer & designer, Independent

Websites, web apps and brand work for churches, NGOs and small businesses.

Founder, GlintSell

E-commerce marketplace. No longer active.

Adoption of artificial intelligence in public health: an umbrella review

A structured umbrella review, following PRISMA-ScR, that synthesises six review studies on how artificial intelligence is being adopted in public health. It went through several rounds of supervisor and committee review before submission. APHTReS conference

AI and digital data systems for family planning: a scoping review

A PRISMA-ScR scoping review for Sub-theme 6 of the conference, on artificial intelligence and digital data systems in family planning. Written with a ten-person team. 9th Nigeria Family Planning Conference (NFPC 2026)

AI-assisted infectious disease screening (2nd place)

Track 1 of the ISS 2026 AI Hackathon. Working in Python with pandas, scikit-learn and Streamlit, we built a screening tool on a dataset released at the event and placed second. IHVN / IRCE 4th Annual Scientific Symposium

PROSKIN project: leprosy and skin NTD surveillance

SIWES placement with The Leprosy Mission Nigeria from January to March 2026, supporting surveillance work on leprosy and other skin neglected tropical diseases. The Leprosy Mission Nigeria

2nd place, ISS 2026 AI Hackathon

IHVN / IRCE 4th Annual Scientific Symposium. Track 1: AI-assisted infectious disease screening, built in Python and Streamlit on a dataset released at the event.