With the next generation of telescopes almost upon us, such as the radio telescope the Square Kilometre Array (SKA) and the optical Rubin Observatory Legacy Survey of Space and Time (LSST), Dr Lochner’s research focus is on rethinking how to do scientific analysis in the era of massive datasets. This largely involves developing new machine learning and statistical tools to best leverage new astronomical data. As one of the South African LSST Principle Investigators, she is working to develop machine learning classification algorithms to handle the billions of new astrophysical transients that LSST will detect. She is also heavily involved in efforts to optimise LSST’s observing strategy, given its many and ambitious science goals. On the radio side, she is interested in a new approach to source-finding and how best to combine optical and radio data, particularly for HI applications such as the LADUMA survey on the SKA pathfinder MeerKAT. Dr Lochner is also particularly interested in the exciting question of scientific discovery in the era where most data cannot be monitored by human eyes and she is working to develop general-purpose anomaly detection techniques for use with LSST, SKA, and other telescopes. Her position is joint between the University of the Western Cape and the South African Radio Astronomy Observatory.
