Discovering radio transients with machine learning and citizen science

Current and upcoming interferometers can now sample wide swathes of the radio sky with unprecedented sensitivity and cadence. As a result, we can now discover radio transients across an immense range of astrophysical regimes $-$ from flare stars to FRBs. I will discuss recent, serendipitous discoveries being made with the MeerKAT radio telescope and how we can make the most of new facilities coming online. This includes how citizen scientists have scoured through commensal data and uncovered 100s of new variable sources. This is the first ever crowdsourcing project dedicated to radio transients in this manner and has uncovered variable sources as different as nearby flare stars, pulsars and AGN. Furthermore, I will discuss the efforts taken to engage communities around South and southern Africa with this work, including a workshop run with young learners from the Northern Cape. Finally I will detail novel machine learning techniques being developed to speed up the search for interesting and anomalous sources, methods that will prove invaluable as we look towards observatories such as the SKA and the data rates that accompany them.