The field of human-centric AI is undergoing significant developments, with a focus on creating more personalized and emotionally aware systems. Researchers are exploring new ways to integrate multimodal perception and advanced language models to improve human-robot interaction and enhance user experience. Notable advancements include the development of systems that can dynamically analyze user emotions and tailor responses accordingly. Another area of focus is on improving data privacy and security, particularly in emerging technologies such as Virtual Reality and Extended Reality. Studies have highlighted the need for more effective privacy controls and awareness campaigns to educate users about the potential risks and benefits of these technologies. Furthermore, researchers are investigating new methods for collecting and annotating emotion data, with a focus on participant-centric approaches and incorporating contextual information. In the realm of data visualization, collective storytelling and audience annotations are being explored as means to create more engaging and relatable visualizations. Some papers have made particularly noteworthy contributions, including the introduction of the PERCY system, which enables open-domain dialogues by analyzing users' real-time facial expressions and vocabulary to tailor responses based on their emotional state. The EQ-Negotiator is another notable example, which combines emotion sensing with emotional reasoning to create a more effective and dynamic negotiation agent.