Curriculum Vitae
Academic Background and Experience
Research-oriented profile spanning neuro-symbolic AI, retrieval-augmented generation, reliability analysis, and teaching in software systems.
Education
- MSc Information Technology (Distinction) - advanced research in LLM and RAG reliability.
- BSc background in computing disciplines - software engineering, machine learning, and systems foundations.
Research Experience
- Designed and evaluated RAG workflows for maternal health decision support.
- Conducted failure-mode analysis for hallucination, grounding, and reasoning inconsistency.
- Developed neuro-symbolic retrieval strategies with explicit safety constraints.
- Investigated utility-aware retrieval objectives for high-stakes AI settings.
Professional Experience
- Teaching Fellow, Strathmore University - courses in mobile development, APIs, and algorithms.
- Applied systems work - distributed architectures, backend integration, and production-oriented engineering workflows.
Skills
- AI/ML: neuro-symbolic AI, RAG, LLM evaluation, hallucination mitigation, safety constraints.
- Systems: distributed systems, backend APIs, data pipelines, reliability testing.
- Programming: Python, Flask, web technologies, model evaluation tooling.
- Research: reproducibility practices, experimental design, technical communication.
Publications
- An Adaptive Game-Based Educational Tool for Maternal and Neonatal Health - ICETT 2025, Seoul (2026).