Hi! Welcome to my personal werbpage! I’m an Assistant Policy Researcher at RAND and a Ph.D. candidate at Pardee RAND Graduate School. You will find updated information about my professional background and RAND-related work here. My interest in R started in 2013 when I was first introduced to it by a professor. Since then, I’ve been using R for virtually everything. From statistical/ML applications to simulation packages (e.g., Arena2R), to modeling competition within the 3D printing industry, R has been my go-to language. In this blog, you will find some R code and tech/R/analytics-related posts that I would like to share with the R community and are not appropriate for a paper. If you find any of this helpful and would like to connect, let me know!
Ph.D. in Policy Analysis, 202X
Pardee RAND Graduate School
Msc in Production Engineering, 2017
UNISINOS University, Brazil
Bsc in Production Engineering, 2015
UNISINOS University, Brazil
This model and tool helps local decision makers understand the impacts of Nonpharmaceutical interventions to tackle COVID-19.
There is an increasing body of knowledge on service quality relationship with many contextual factors, including culture, firm size, and public vs. private settings. However, local socioeconomic factors influence towards SMEs Service Quality is still unknown. We conducted statistical analyzes to observe the relationship between contextual socioeconomic factors of an SMEs city and its services quality performance using a SERVPERF survey database of more than 3,000 Brazilian SMEs. While Service Performance did not linearly correlate with the analyzed socioeconomic factors, a closer look at the data shows significant differences in Service Performance among groups of SMEs on highly developed and underdeveloped cities from the other cities. The paper discusses theoretical and managerial implications derived from these findings and proposes new research questions to generate data-backed knowledge to support SMEs service quality improvement.
I’ve been working on many exciting policy research projects, usually using R and simulation modeling to build decisions support tools. These projects include:
Taught the following disciplines in undergraduate and MBA classes:
Simulation Modeling (Discrete Event Simulation & Systems Dynamics);
Operations Research - Linear Programming;
Information Systems Management;
Advised undergraduate and MBA students in their capstone research projects, one of which received the Best Brazilian Production Engineering Undergraduate Dissertation Award from ABEPRO (2019).
Durante o meu tempo como como professor na UNISINOS no curso de Engenharia de Produção, acumulei uma boa quantidade de slides. Provavelmente não vou utilizar estes slides nos próximos 5 anos, portanto nada mais razoável do que compartilhar!
Teaching to seasoned managers in MBE classes is challenging. While it’s important to bring new thoughts and ideas and not sound repetitive, it is necessary to provide a theoretical basis for experienced people with diverse backgrounds.
Simulation Metamodeling - building and using surrogate models that can approximate results from more complicated simulation models - is an interesting approach to analyze results from complicated, computationally expensive simulation models.
This is part 1 of a series of posts in which I will explore the utility of using metamodels to make sense of (and possibly optimizing) simulation models. If you used simulation modeling on a real project, you might be familiar with this fictional story:
This post contains materials related to the the presentation given at the 2018 DMDU Annual Meeting. Full Master’s Thesis: Donwload Here. Slides: Donwload Here. Poster: Donwload Here.