Mugume Twinamatsiko Atwine

Mugume Twinamatsiko Atwine is a dedicated Data Scientist with over a decade of expertise in computer science with a background in computer Science with a BSc and MSc in Computer Science, specializing in machine learning, deep learning, natural language processing and MLOps. He is passionate about leveraging technology to advance health equity and drive social impact, particularly in resource-constrained environments. As a Health Data Scientist and ML Engineer at the Infectious Diseases Institute and ACE Uganda (since June 2020), I contribute to the DS-I Africa consortium and eLwazi open data science platform, and lead the OHDSI Uganda chapter, implementing the OMOP Common Data Model to strengthen regional evidence generation. A central thread is building AI systems in African languages. I led development of COAST, a bilingual English-Luganda COVID-19 chatbot that processed over 200,000 citizen queries, published in PLOS Digital Health (2026). Other applied work includes the SIDA Risk AI tool for HIV risk evaluation among youth, social media network analytics for pandemic information flow, and LLM-based clinical decision support. I also contribute to research infrastructure and capacity building, co-authoring publications on scalable HPC frameworks, sustainable HPC guidelines , NIH-supported bioinformatics training impact (Briefings in Bioinformatics, 2026), and generative AI for LMIC challenges, plus the open-source Metadata Harmonisation Tool. I hold an MSc in Computer Networks (Limkokwing University, Malaysia) and a BSc in Computer Science (Mbarara University, Uganda), with additional data science certifications.