Human activity recognition with radar sensors has attracted a lot of attention, starting initially from fall detection and moving to the classification of more complex patterns of activities as well as hand gestures and vital signs. While initial research in this domain considered activities and human body movements as artificially separated, individual ‘snapshot-like’ data, more recent work explores techniques that can deal with more realistic, unconstrained sequences of continuous activities. This talk will briefly overview recently proposed research and radar-based human activity recognition techniques, focussing on the radar signal processing tools and machine learning techniques proposed in the state-of-the-art literature. Speaker(s): Dr. Francesco Fioranelli Virtual: https://events.vtools.ieee.org/m/369295