SNU Causal Inference Lab

연구실 소개

The SNU Causal Inference Lab develops design- and algorithm-centric methods for causal inference, with a focus on matching, weighting, diagnostics, and randomization-based inference. This lab conducts research on the theory and methodology of statistical causal inference. We primarily focus on the design and analysis of experimental or observational studies that can effectively and accurately infer causal relationships. For example, we conduct research to create design strategies that minimize the impact of unobserved confounding variables on the analysis process. In the analysis process, we discover heterogeneous effects to enhance the understanding of treatment effects and research methodologies that enable effective estimation. This research can be applied to various disciplines such as medicine, public health, and social sciences, providing important insights into diverse problems.