System Engineering

System engineering is evolving to address the challenges posed by increasingly complex systems, particularly those incorporating machine learning (ML). Current research focuses on integrating ML components into established engineering lifecycles, developing formal methods for specifying and verifying ML-based systems, and addressing the assurance and safety challenges inherent in these systems, including defining and managing software end-of-life. This work is crucial for ensuring the safe and reliable deployment of AI-powered systems across various sectors, from autonomous vehicles to critical infrastructure, and for establishing robust standards and regulations for their development and certification.