Keynote speak: Danijela Cabric - Integrating Intelligence into Wireless Systems: Learning for Spectrum Awareness, Spatial Prediction, and Robustness to Hardware Impairments

Next-generation wireless systems are evolving beyond the pursuit of higher data rates toward intelligent radio networks capable of supporting dense user connectivity, improved spectral efficiency, and integrated sensing and communication. Under this vision, wireless infrastructure is expected not only to exchange information but also to sense, localize, and adapt to the surrounding environment. In this talk, I will present recent research on integrating intelligence into wireless systems through three representative applications. First, I will discuss AI-driven approaches for wideband spectrum sensing that combine signal detection, classification, and RF fingerprinting using complex-valued neural networks. Second, I will present learning-based techniques for user localization, tracking, and spatial prediction based on deep learning, hypernetworks, and in-context learning. Third, I will discuss in-context learning approaches for sample-efficient adaptive self-interference cancellation, enabling robust full-duplex operation under realistic hardware impairments and time-varying conditions. Finally, I will introduce ongoing research on learning-enabled channel estimation and super resolution angle-of-arrival estimation in large-scale MIMO systems.