The fields of interactive visualization, human-centric technologies, and artificial intelligence are undergoing significant developments, driven by the need for more effective data exploration, improved human performance, and enhanced safety. Researchers are exploring innovative approaches to facilitate more intuitive and engaging data analysis, including the use of augmented reality (AR) and virtual reality (VR) technologies, tangible user interfaces, and multimodal interactions. Notable papers in this area include A Design Space for Visualization Transitions of 3D Spatial Data in Hybrid AR-Desktop Environments, Coordinated 2D-3D Visualization of Volumetric Medical Data in XR with Multimodal Interactions, and 2024 NASA SUITS Report: LLM-Driven Immersive Augmented Reality User Interface for Robotics and Space Exploration. Meanwhile, the field of human-centric technologies is focusing on improving human performance, reducing errors, and enhancing situational awareness in high-stakes environments. A key direction is the integration of artificial intelligence, machine learning, and data-driven methodologies to support human decision-making and optimize system performance. Noteworthy papers in this area include Building Trustworthy Cognitive Monitoring for Safety-Critical Human Tasks, A New Perspective On AI Safety Through Control Theory Methodologies, and InSight-R: A Framework for Risk-informed Human Failure Event Identification and Interface-Induced Risk Assessment Driven by AutoGraph. The field of software engineering is shifting towards a more human-centered approach, with a growing focus on the experiences and well-being of developers, users, and other stakeholders. Recent research has highlighted the importance of accessibility, inclusivity, and social learning in software development, as well as the need for more effective support systems for developers and users. Notable papers in this area include Towards a Science of Developer eXperience (DevX) and Is It Safe To Learn And Share? On Psychological Safety and Social Learning in (Agile) Communities of Practice. The field of artificial intelligence is moving towards a greater emphasis on safety and responsibility, driven by the increasing capabilities and potential risks of foundation models. Researchers are exploring new approaches to AI safety, including the development of open-source tools and participatory mechanisms for mitigating potential harms. Noteworthy papers in this area include A Different Approach to AI Safety and The Societal Impact of Foundation Models. Overall, these advancements have the potential to revolutionize the way we approach data analysis, improve human performance, and enhance safety in various contexts. As research in these fields continues to evolve, we can expect to see more innovative solutions and applications that transform the way we live and work.