Dr. Samuel Kizito is a physician, infectious disease epidemiologist, and biostatistician whose research bridges clinical practice and advanced quantitative methods. His work centers on two key areas: (1) developing and evaluating interventions to address structural barriers and improve access to and adherence to HIV treatment among children and adolescents in low-income settings, and (2) applying advanced statistical and methodological approaches to the design and analysis of intervention studies involving longitudinal and clustered data.

Dr. Kizito has expertise in a wide range of analytic techniques, including mixed-effects modeling, latent class analysis, generalized linear modeling, generalized estimating equations, survival analysis, structural equation modeling, latent growth curve modeling, predictive modeling, and Machine Learning. His research has been published in high-impact journals such as The Lancet, BMJ, and Nature Communications.