The recent advancements in the research area are significantly shaping the future of public service management, criminal justice scheduling, and energy grid flexibility. There is a notable shift towards optimizing service level agreements (SLAs) in government operations to ensure both equity and efficiency, leveraging queuing network frameworks and simulation-optimization techniques. This approach not only theoretically validates the minimal 'price of equity' but also empirically demonstrates substantial improvements over current practices in cities like New York. In the realm of criminal justice, there is a growing emphasis on fair pretrial scheduling systems that consider defendants' preferences and availability, addressing the logistical challenges through joint optimization and learning frameworks. These systems aim to balance the needs of all parties involved, thereby enhancing the fairness and efficiency of court processes. Additionally, the integration of AI and high-performance computing (HPC) data centers is revolutionizing power grid management. AI-focused HPC data centers are shown to provide greater flexibility at significantly lower costs compared to traditional HPC centers, contributing to more efficient power system balancing and offering profitable market opportunities. Lastly, the synergistic collaboration between data centers and local energy communities is being explored to optimize waste heat usage and market participation, resulting in substantial cost reductions and enhanced energy efficiency.