A meticulously curated collection of cutting-edge research, frameworks, and methodologies in Causal Artificial Intelligence.

Official reproducibility experiments of the Thesis "Large Causal Models for Temporal Causal Discovery" at the University of Crete, Computer Science Department.

Causal inference methods for -omics research

Weighted doubly robust learning for uplift modeling

A simple way to visualize discrepancies between causal matrices of true and predicted directed acyclic graph

My Master's dissertation, Large Causal Models for Temporal Causal Discovery.

Causal inference project using DoWhy to isolate the true marketing lift of bank contact methods. Applies Propensity Score Stratification to remove selection bias from raw campaign data and delivers an interactive ROI simulator for budget decision-making.