The research in signal processing at our school ranges from the development of new generic, fundamental tools for statistical signal processing to cutting-edge signal processing algorithms serving diverse applications in signal analysis and parameters estimation. Generic tools include new forms of high-order statistics and their optimized deployment in general estimation problems, development and analysis of performance bounds for Independent Component Analysis (ICA) and Blind Source Separation (BSS), along with optimal algorithms which attain these bounds. Applications include passive and active modern emitter location approaches, accounting for multipath effects, mis-synchronization and outlier mitigation in multi-sensors network, as well as Direct Position Determination (DPD). Another emerging application attracting research activity at our school is the use of microwave-links attenuation data, obtained from cellular communication providers, for monitoring and classifying precipitation. Additional research areas include speech processing, auditory sensory systems modeling and analysis, sparsity-based signal processing and machine-learning approaches for signal processing.