The field of human-centric technologies and safety-critical systems is experiencing significant developments, driven by the need for more efficient, reliable, and safe systems. Researchers are exploring innovative approaches to improve human performance, reduce errors, and enhance situational awareness in high-stakes environments, such as air traffic control, healthcare, and maritime operations. A key direction is the integration of artificial intelligence, machine learning, and data-driven methodologies to support human decision-making and optimize system performance. Another important area of research focuses on the development of immersive technologies, such as virtual and augmented reality, to enhance training, education, and human-machine collaboration. Noteworthy papers in this area include: Building Trustworthy Cognitive Monitoring for Safety-Critical Human Tasks, which presents a phased methodological approach to building cognitive monitoring systems. A New Perspective On AI Safety Through Control Theory Methodologies, which outlines a new perspective on AI safety based on an interdisciplinary interpretation of the underlying data-generation process. InSight-R: A Framework for Risk-informed Human Failure Event Identification and Interface-Induced Risk Assessment Driven by AutoGraph, which proposes a framework for risk-informed human failure event identification and interface-induced risk assessment. A Comprehensive Review of Human Error in Risk-Informed Decision Making, which synthesizes recent advances at the intersection of risk-informed decision making, human reliability assessment, artificial intelligence, and cognitive science to clarify how their convergence can curb human-error risk.