The field of power system security and control is moving towards the development of innovative methods to quantify and enhance the security of uncertain interconnected systems. Researchers are exploring new approaches to provide probabilistic dynamic security assessments, considering factors such as load and generation variability, and uncertain cascade propagation. Additionally, there is a growing interest in leveraging physics-informed learning and data-driven techniques to improve passivity-based tracking control and estimate power system parameters such as inertia. Noteworthy papers include: Security Metrics for Uncertain Interconnected Systems under Stealthy Data Injection Attacks, which proposes a novel approach to quantify the security of uncertain interconnected systems under stealthy data injection attacks. Towards Probabilistic Dynamic Security Assessment and Enhancement of Large Power Systems, which presents a methodology for probabilistic dynamic security assessment and enhancement of power systems considering various factors. Physics-informed Learning for Passivity-based Tracking Control, which introduces a data-driven tracking control approach based on physics-informed models to address the limitations of traditional passivity-based control methods. A Practical Approach Towards Inertia Estimation Using Ambient Synchrophasor Data, which proposes a practical method to estimate inertia using ambient phasor measurement unit data. Impact of Grid-Forming Inverters on Protective Relays, which analyzes the interaction between grid-forming inverters and protective relays, providing insights into the design of current limiting control for grid-forming inverter-based resources.