The field of power grid research is currently moving towards addressing the challenges of grid stability and optimization in the face of increasing complexity and volatility. Researchers are exploring new frameworks and approaches to analyze and control grid-forming converters, optimal transmission switching, and transient slack capability. Notably, the development of innovative tools and methodologies, such as dynamic phasor frameworks and open-source learning toolkits, is enabling more accurate and efficient analysis and optimization of power grid operations. Some noteworthy papers include: The Dynamic Phasor Framework for Analysis of Grid-Forming Converter Connected to Series-Compensated Line, which proposes a novel framework for analyzing grid-forming converters. PGLearn, an open-source learning toolkit for optimal power flow, which provides standardized datasets and evaluation tools for ML and OPF.