The field of control and estimation of complex systems is rapidly advancing, with a focus on developing innovative methods for analyzing and controlling networked dynamical systems, nonlinear feedback systems, and distributed systems. Recent research has led to the development of new frameworks and techniques for inverse inference, graphical dominance analysis, and soft and hard scaled relative graphs. These advances have significant implications for a wide range of applications, including clock skew compensation, atomic time scale generation, and distributed observer design. Noteworthy papers include: Inverse Inference on Cooperative Control of Networked Dynamical Systems, which proposes a bi-level inference framework for estimating global closed-loop systems. Explicit Ensemble Mean Clock Synchronization for Optimal Atomic Time Scale Generation, which presents a novel framework for atomic time scale generation that unifies clock synchronization and time scale generation within a control-theoretic paradigm.