The field of complex systems management is undergoing significant transformation with the integration of digital twins and real-time analytics. This shift is driven by the need for more efficient, resilient, and sustainable systems across various domains, including air traffic management, supply chain optimization, and data center operations. Researchers are exploring innovative applications of digital twins, such as graph-based modeling for supply chain management and physical AI for data center operations, to enhance decision-making, reduce costs, and improve overall system performance. Noteworthy developments include the use of digital twins for personalized elder care and the development of methodologies for bridging research and standardization in next-generation networks. Notable papers in this area include: A paper on a theoretical framework for graph-based digital twins for supply chain management, which proposes a scalable and adaptable approach to optimizing supply chains. A paper on transforming future data center operations via physical AI, which presents a novel framework for advancing data center management using state-of-the-art industrial products and in-house research.