picture1I am an ABD graduate student of Political Science and Scientific Computing, with a dual degree in Statistics, at the University of Michigan, Ann Arbor. Before my Ph.D. in Political Science, I studied mathematics and computer science at the School of Mathematics and Computer Science (ICMC) at the University of Sao Paulo (USP) and social sciences at the School of Philosophy, Literature and Human Sciences (FFLCH) at the same university.

Currently (2018), I am working with political methodology and political economy of distributive politics. On the methods side, I am interested in developing empirical (statistical) and formal (analytical) models to study the politics of redistribution. I understand empirical modeling as the application of mathematical statistics to develop theory-oriented probabilistic models intended to account for the underlying data generating process. I am particularly interested in semi-parametric density estimation, models for dependent data, and modeling effect heterogeneity using stochastic processes. Semiparametric models provide a rich class of model-based clustering techniques to deal with latent effect heterogeneity. Such models have wide applicability in social sciences and also in other disciplines that use quantitative data analysis.

On the substantive side, I am interested in comparative analysis of preferences for redistribution as well as the relationship between economic development, inequality, and political behavior. I have developed and used models with a latent structure to investigate individuals support for redistribution in comparative perspective. I also have studied the effect of electoral competition and legislative bargain on the adoption of redistributive programs in multiparty systems.