Giovanni Malloy is a researcher at the RAND Corporation with expertise in data science, artificial intelligence, decision analysis, mathematical modeling, and simulation. In his research, he develops new methods and leverages existing methods, such as machine learning, deep learning, data analytics, economic modeling, and complex networks, to evaluate policy interventions. At RAND, his work has focused on machine learning, advanced data analytics, AI technology evaluation, forecasting, modeling, and simulation for the Army, Air Force, and law enforcement. 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.
Malloy, G.S.P. and Brandeau, M.L., "When is mass prophylaxis cost-effective for epidemic control? A simple decision rule," Medical Decision Making, 42(8), 2022
Malloy, G.S.P., Puglisi, L.B., Brandeau, M.L., Harvey, T.D., and Wang, E.A., "The effectiveness of interventions to reduce COVID-19 transmission in a large urban jail: A model-based analysis," BMJ Open, 11(2), 2021
Malloy, G.S.P., Brandeau, M.L., and Goldhaber-Fiebert, J.D, "Modeling the cost-effectiveness of interventions to prevent plague in Madagascar," Tropical Medicine and Infectious Disease, 6(2), 2021
Malloy, G.S.P., Goldhaber-Fiebert, J.D., Enns, E., and Brandeau, M.L., "Predicting the effectiveness of endemic infectious disease control interventions: The impact of mass action versus network model structure," Medical Decision Making, 41(6), 2021
Malloy, G.S.P.*, Puglisi, L.B.*, Harvey, T.D., Brandeau, M.L., Wang, E.A. , "Estimation of COVID-19 basic reproduction ratio in a large urban jail in the United States," Annals of Epidemiology, 53, 2021