With more than 15 years of experience applying AI-driven analytics in global health and clinical research, Dr. Onovo excels in developing and deploying machine learning models—including Extreme Gradient Boosting, DNNs, and Bayesian techniques—to enhance prediction accuracy, guide resource allocation, and drive impactful, data-driven strategies. Dr. Onovo has led the design and implementation of data visualization tools (Tableau, Power BI, GIS) and strategic health information systems, resulting in a 30% increase in data-driven decision-making for global health programs. Dr. Onovo's work includes building AI-powered risk prediction models for HIV/AIDS, stroke, and treatment adherence on cloud platforms such as AWS and Hugging Face, reaching over 50,000 users and influencing public health policy decisions that affect more than 300,000 individuals. Through advanced statistical modeling, predictive analytics, and effective M&E frameworks, Dr. Onovo is committed to leveraging data science for meaningful, large-scale improvements in health outcomes.