Associate Professor of Biostatics and Research
Dr. Ratnasiri brings exceptional research expertise in developing advanced risk predictive models. His work focuses on analyzing large, longitudinal, population-based datasets that integrate diverse data types to identify critical predictors of morbidity and mortality. By leveraging machine learning, Dr. Ratnasiri bridges gaps in descriptive and predictive analytics within public health data, uncovering patterns and trends often overlooked by traditional methods. His innovative approach advances our understanding of complex health outcomes and informs strategies to improve public health.
Throughout his career, Dr. Ratnasiri has collaborated with renowned institutions, including Stanford University School of Medicine, UCSF, UC Davis, and Leiden University in the Netherlands. His impactful research has resulted in numerous successful publications that have received significant recognition and citations.
Dr. Ratnasiri’s research spans pivotal areas such as the Fetal Origin of Adult Diseases (Barker’s hypothesis), Life Course Trajectory, and Epigenetics, highlighting the profound influence of early life experiences on long-term health outcomes. He also prioritizes addressing Social Determinants of Health, promoting Health Equity, and reducing Health Disparities. Dr. Ratnasiri excels in translating complex population-based data into actionable insights. His overarching vision is to contribute to a healthier future generation by addressing the root causes of health disparities and strategically redirecting resources to improve social determinants of health. He aspires to create a more equitable and sustainable healthcare landscape, where good health is not only a possibility but a reality accessible to all.