Kameta Oghenetega Samuel
MSc Data Science Researcher and Applied AI Builder, University of Ghana
MSc Data Science (current), University of Ghana; Applied AI builder and technology entrepreneur
- Research programme
- Data Science, Statistical Intelligence & Decision Systems
Biography
Kameta Oghenetega Samuel is an MSc Data Science researcher at the University of Ghana whose work sits at the intersection of data science, Artificial Intelligence and real-world African infrastructure challenges.
Based in Accra, Ghana, his research combines computational modelling with a strong engineering orientation: he is interested not only in understanding complex problems through data, but also in building systems capable of operating in the environments being studied.
His MSc thesis, "Diagnosing Road Network Congestion in Accra," investigates urban traffic congestion across six major Accra corridors through a continuously operating data pipeline, structured field observations and anomaly-detection methods.
His second emerging research direction investigates how clinical Natural Language Processing systems interpret informal West African patient language, particularly how women describe fibroid symptoms online and how existing clinical NLP approaches respond to those descriptions.
Beyond research, Kameta is an active technology builder. He has developed and deployed live software products serving African users, including business-management software for merchants in Ghana and Nigeria and an AI-powered nutrition application designed around West African diets.
At DRAKA Labs, Kameta contributes an emerging capability in Urban Intelligence, African AI, real-time data systems and research-to-deployment experimentation, reflecting DRAKA Labs' emphasis on applied computing research and research translation.
Research interests
- Urban Data Science
- Urban Intelligence
- Anomaly Detection
- Real-Time Data Systems
- Intelligent Infrastructure
- Clinical Natural Language Processing
- Culturally Responsive AI
- AI Evaluation
- African Language & Context-Aware AI
- Applied Machine Learning
- Research-to-Deployment
- Digital Health
Research programme leadership
Data Science, Statistical Intelligence & Decision Systems
Applied domains
- Traffic congestion diagnosis
- Urban mobility analysis
- Flood early warning
- Smart-city systems
- Infrastructure monitoring
- Clinical NLP evaluation
- Digital health tools
- Merchant business software
- AI nutrition applications
- Operational anomaly detection
Professional expertise
- Urban Data Science
- Anomaly Detection
- Real-Time Data Systems
- Time-Series Analysis
- Applied Machine Learning
- Clinical NLP
- Culturally Responsive AI
- Software Engineering
- Product Deployment
DRAKA Labs responsibilities
- 01Contribute emerging research in Urban Intelligence, African AI, real-time data systems and research-to-deployment experimentation
- 02Operate live data pipelines and combine computational analysis with structured field observation for urban mobility research
- 03Develop anomaly-detection methods to diagnose unusual congestion behaviour across Accra corridors
- 04Investigate how clinical NLP systems interpret informal West African patient language, and evaluate AI in context
- 05Advance culturally responsive, context-aware AI evaluation for African linguistic and institutional environments
- 06Use working, deployed systems as instruments for learning, measurement and research (deploy-to-learn)