Samuel Iddi

Samuel Iddi is a trained and experienced biomedical scientist, biostatistician, and data scientist with a rich research portfolio, underpinned by statistical/methodological research and the application of innovative research techniques to advance public health and biomedical research. He currently works as a research scientist and data scientist at the African Population and Health Research Center (APHRC), managing data science projects that employ machine and deep learning to address problems related to the multimorbidity of non-communicable diseases. Samuel’s career research in the development of statistical methods has led to novel methods for handling overdispersion, inflation of zero counts, jointly modelling longitudinal outcomes, models for marginalised inference, etc. His research works have also influenced and informed statistical practices. He is a recognised trainer in statistical software, statistical methods, data management and analysis, impact evaluation methods, etc., and has provided training workshops and mentorship for researchers and students. In 2013, he got his PhD from the University of Leuven, Belgium, in Biomedical Sciences (Biostatistics).