This is a space where I share my work and ideas at the intersection of ecology, statistics, and econometrics. My research focuses on applying Bayesian and probabilistic modeling techniques to real-world data, particularly in the context of ecological systems and environmental change. I’m especially interested in how we can account for uncertainty, bias, and incomplete observations—challenges that are common in both ecological and social science data.
A major part of my work involves analyzing citizen science datasets, such as those from iNaturalist and PlantNet, which offer valuable insights into species distributions but require careful statistical treatment due to their presence-only nature. Alongside ecological applications, I also explore econometric approaches to survey data, where issues like sampling design, missing data, and model specification play a critical role in extracting meaningful conclusions.