State estimation is a fundamental research area and methodological approach focused on inferring the internal state of a dynamic system based on a sequence of potentially noisy or incomplete measurements. This field investigates techniques to combine system models with observed data to produce optimal or near-optimal estimates of unmeasured variables, which is crucial for tasks such as system control, monitoring, diagnostics, and prediction across diverse engineering and scientific disciplines.