The University's research into Astrophysics covers a wide range of modern astrophysics. We have particular expertise in radio-mm observational astronomy but we also make observations at a wide range of other wavelengths and combine these with theory and modelling.
The Pulsars and Time Domain Astrophysics group are using innovative methods for processing high data volumes in radio astronomy, this includes energy efficient computing, heterogeneous computing architecture and optimised algorithms. The group are also generating machine learning approaches to filter the results of their analyses.
Ben's primary research interests include radio pulsars, neutron stars and rapid radio transients. He's a co-PI of the pulsars and fast transient project TRAPUM which will run on the MeerKAT Telescope a precursor to the Square Kilometer Array (SKA) radio telescope and is involved in the specification of various aspects of the SKA itself. The group is currently undertaking the design work for the pulsar and fast transient search capabilities of the SKA.
Ben has previously collaborated with the Machine Learning and Optimisation group. Currently, he is working on generating machine learning approaches to the data so they are able to filter the amount of data generated to a manageable and useful level and allow for accurate decision making in real time on the streamed data.