Giovanni Malloy is a researcher at the RAND Corporation with expertise in data science, decision analysis, mathematical modeling, and simulation. In his research, he develops new methods and leverages existing methods, such as machine learning, artificial intelligence, data analytics, economic modeling, and complex networks, to evaluate policy interventions. Specifically, his dissertation focused on developing computational models and improving analytical methods for guiding health policy decision making. Applications of his work include COVID-19 mitigation in jails and prisons, structural sensitivity analyses, cost-effectiveness analyses, and developing analytical and metamodel alternatives to traditional model archetypes. He holds a Ph.D. in Management Science & Engineering from Stanford University and a BS in Industrial Engineering from Purdue University.