I am a PhD candidate working on causal inference methods at the Real World Evidence Team, Department of Data Science & Biostatistics, UMC Utrecht.
My PhD focuses on causal inference with observational data. My current focus is the comparison of confounder adjustment methods and the application on target trial emulation in challenging contexts.
My aim is to understand how we can use large-scale electronic health records to study the safety and effectiveness of health interventions, especially for questions where randomized clinical trials are unlikely to be performed.
About
I graduated from the Methodology and Statistics Research Master’s at Utrecht University. During my studies, I helped developing the densityratio R package, I was part of the ODISSEI Social Data Science Team, and I was a teaching assistant for different courses. My Master’s thesis focused on the development of a Bayesian implementation of the synthetic control method.
Before, I worked for three years as a researcher in survey methodology at RECSM-UPF. There, we used latent variable models to estimate measurement error and assess measurement comparability of data from the European Social Survey.
Originally from Galicia, I am now based in Utrecht.