Md Roungu Ahmmad

Md Roungu Ahmmad is an Assistant Professor of Biostatistics and Data Science at the University of South Florida's College of Nursing. His academic journey includes a PhD and MS in Biostatistics and Data Science from the University of Mississippi (2022 and 2020), a Professional Certificate in Statistical Genetics from the University of Washington (2022), and earlier degrees (MSc and BSc) in Statistics Biostatistics and Informatics from the University of Dhaka (2010 and 2008).

His research interests focus on advancing statistical and data science methodologies to address complex questions in biomedical, epidemiologic, and public health research. Dr. Ahmmad's work lies at the intersection of biostatistics, machine learning, and population health, with emphasis on cancer epidemiology and the exposome, neurodevelopmental disorders, chronic disease modeling, and large-scale data analysis. He develops predictive and causal models to understand how environmental exposures interact with genetic and behavioral factors to influence health outcomes, particularly in underserved populations.

His recent publications demonstrate a strong trend toward analyzing health disparities using population-level data (SEER, NHANES, NSCH, cBioPortal), with particular focus on cancer outcomes, autism spectrum disorder, obesity-related health outcomes, and the impact of social factors during the COVID-19 pandemic. His methodological approach integrates supervised and unsupervised learning techniques with traditional biostatistical models to improve early detection, risk prediction, and outcome classification.

Dr. Ahmmad is a member of the American Statistical Association (since 2007) and believes that responsible and innovative application of statistical science has the power to transform public health. His research philosophy emphasizes transparency, rigor, and collaboration, with commitment to promoting health equity and using data to inform ethical, evidence-based policies and interventions.

His collaborative, interdisciplinary research is geared toward improving health outcomes, especially among vulnerable and underrepresented populations. His work contributes to the development of reproducible and interpretable models that inform evidence-based decision-making in public health, clinical practice, and health policy.