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Dr. Koomson has research interests in statistical methodology, count data modeling, data mining, and statistical machine learning. His work focuses on developing robust and efficient methods, including zero- and multiple-inflated count data models, as well as variable selection. He aims to advance methodological tools for analyzing complex count data and extracting meaningful insights across diverse domains with applications in Health.