I am a doctoral researcher and research assistant at TU Dortmund University, working with Paul Bürkner. Previously, I was a research assistant at the Cluster of Excellence SimTech at the University of Stuttgart. I hold a Master’s degree in Probability and Statistics from the Center for Research in Mathematics (CIMAT) in Guanajuato, Mexico, where I was supervised by Andrés Christen.
My research focuses on Bayesian computation, prior specification, probabilistic programming, and high-dimensional statistics. My work has been published in journals such as Bayesian Analysis, Statistics and Computing, and the Electronic Journal of Statistics, and is also available as preprints on arXiv. A central theme of my work is using interpretable, problem-specific quantities as the foundation for constructing joint prior distributions in high-dimensional models. I also create methods for controlling model complexity, improving uncertainty quantification, and enhancing model validation through simulation-based techniques. To help researchers apply modern Bayesian methods effectively in their own work, I teach and organize workshops on Bayesian data analysis and the use of brms, an R package for Bayesian regression modeling using the probabilistic programming language Stan. These have included events at institutions such as Charité, Freie Universität Berlin, Humboldt University of Berlin among others. I also collaborate with applied scientists in fields such as biostatistics and the natural sciences, adapting and implementing these methods in real-world studies. I am currently exploring postdoctoral opportunities in these areas and welcome discussions about potential collaborations or openings.
I’m always happy to connect. Feel free to reach out if you’d like to discuss Bayesian methods, potential collaborations, or just exchange ideas.