STSELab PhD student Shefa presented her research on building causal interpretability into system health prognostics and management models. The core idea is to unpack black-box AI/ML algorithms that are commonly used for this purpose for increased transparency, enabling trustworthy and proactive decisions for system operations and sustainment.