Kevin Chetty is an Associate Professor at University College London. His research expertise lies in the field of radio-frequency (RF) sensing, and radar signal processing using machine learning. Major achievements in RF sensing include demonstrating the first detections of personnel targets using passive WiFi radar, and proving the ability of these systems to perform through-the-wall sensing at standoff distances. In the signal processing domain Kevin’s work has focused on classifying peoples actions based on their radar micro-Doppler signatures for applications in both security and e-healthcare. His work in this area also covers indoor mapping, target tracking, and high-throughput data processing. Kevin is author to over fifty peer reviewed publications and has been an investigator on grants in passive wireless sensing and FMCW radar for microDoppler target classification funded by EPSRC, EU Joint Research Centre, UK Ministry of Defence/Dstl and the UK Maritime & Coastguard Agency. He also sits on the Technical and Organising Committees for the International Security & Crime Science conference and is a member of the IEEE and IET, and reviewer for a number of high-esteem journals including: IET Radar, Sonar and Navigation; IEEE Geoscience & Remote Sensing; and IEEE Communications magazine.