Pedro Nascimento de Lima

Pedro Nascimento de Lima is a Professor at the RAND School of Public Policy and an Engineer at the RAND Corporation. He specializes in computational methods to inform policy decisions, with expertise in Robust Decision Making, Modeling and Simulation, and Health Economics. His research addresses complex policy domains including healthcare, pandemic response, and systemic risk assessment. He holds a Ph.D. in Policy Analysis from RAND, and B.S./M.S. in Production Engineering from Universidade do Vale do Rio dos Sinos (Brazil).

Key contributions include developing the modeling framework for RAND's widely-used COVID-19 State Policy Tool, stress-testing colorectal cancer screening guidelines, and advocating for sustained wastewater surveillance capabilities. His work integrates advanced computational tools with open-source contributions, emphasizing reproducibility and policy robustness. Recent research focuses on evaluating AI capabilities, improving causal inference methods, and assessing cost-effectiveness of health interventions.

Notable projects include Bayesian calibration of cancer microsimulation models, analysis of non-pharmaceutical interventions during the pandemic, and exploring policies to address wealth disparities. He collaborates with institutions like Argonne National Laboratory for high-performance computing applications in health policy modeling.