Dr. Yaesoubi’s research focuses on medial decision making and model-based evaluation of health policies. His work incorporates mathematical and computer simulation models, machine learning methods, and optimization techniques to guide resource allocation and decision making in public health and health delivery systems. He has applied these methods in estimating the impact of different strategies to reduce the prevalence of alcohol-exposed pregnancies, conducting cost-effectiveness analyses of colorectal cancer screening strategies, estimating societal willingness-to-pay for health, and characterizing performance-based payment systems for preventive care systems. His current work mainly focuses on optimizing public health responses to control the spread of infectious diseases including COVID-19, influenza, meningitis, and drug-resistant tuberculosis and gonorrhea. He is also interested in theoretical and methodological issues in medical decision-making and health care resource allocation.