"Reproducible workflows for research papers" with Dr. Seo-young Silvia Kim

For the January 25th edition of our R-Ladies Dallas webinar series, we are excited to welcome Dr. Seo-young Silvia Kim as our guest speaker. Dr. Kim will introduce the topic of reproducible workflows for research. Although the term "research" brings thoughts of academic research to mind (for example, a dissertation or thesis), these ideas are also directly applicable to other workflows that professional data scientists and analysts encounter in their daily work. Whatever your role, we hope you will come ready to enhance your understanding and appreciation of reproducible workflows and feel empowered to apply this framework in your research.

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Session title: Reproducible Workflow When Writing a Research Paper
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Abstract: College and Ph.D. students who do empirical work often underestimate the problems associated with reproducibility. Certain lessons should be shared for those entering the research phase, which will help not to struggle or waste time later. From setting up an R project to using renv, I discuss some of the most important things that new researchers should be mindful of when starting a new data analysis project.

Bio: I am an Assistant Professor in the Department of Government at American University. I received my Ph.D. from the California Institute of Technology in 2020. My research interests are in American Politics and Political Methodology, focusing on political behavior (registration/turnout/campaign contributions), working with large voter files and Federal Election Commission datasets. I mainly use R and Stan to employ tools such as probabilistic record linkage, semiparametric regressions, machine learning, and Bayesian statistics.

Twitter: @sysilviakim

Website: sysilviakim.com

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