Our research focuses on the development and implementation of advanced statistical methods to make informed decision, improve health outcomes and strengthen evidence-based practices. 

We are particularly interested in advancing statistical methods to inform decision/makers and regulatory assessors where evidence cannot be derived from randomized studies due to ethical reasons or when decisions are mainly based on single arm studies. We are working on the methodological development of G-methods in a flexible Bayesian framework to address issues related to spatial correlation in the data for a better estimation of causal contrasts of interests.

We also provide support in the analyses of individual and cluster randomized trials, including trials with innovative design such as Trials within Cohorts (TwiCs), platform trials, and stepped wedge designs.