Recently, the machine learning and deep learning methods have been applied to radar signal processing and imaging, which can be classified as model-based (such as statistical methods) and data-learning (such as deep neural networks) techniques. In comparison with the model-based approaches, the learning algorithms benefiting from the advanced processing framework and a flood of valuable radar data are more adaptive, robust to the data with high efficiency for superior performance. This session focuses on the latest developments and advances of the machine learning and deep learning frameworks on radar signal processing and imaging. The topics includes (but are not limited to) array signal processing, MIMO radar, ISAR imaging, SAR imaging, metamaterial imaging and etc.