Dr Michelle Lochner, Senior Lecturer in Astrophysics at the University of the Western Cape, South Africa, will be presenting a paper titled Anomaly Detection in Astronomical Data using Machine Learning.

The next generation of telescopes such as SKA and the Vera C. Rubin Observatory will produce enormous data sets, far too large for traditional analysis techniques. Machine learning has proven invaluable in handling large data volumes and automating many tasks traditionally done by human scientists. In this talk, Dr Lochner will discuss how machine learning for anomaly detection can help automate the process of locating unusual astronomical objects in large datasets thus enabling new cosmic discoveries. She will introduce Astronomaly, a general purpose framework for anomaly detection in astronomical data using active learning and overview some recent results.

This seminar may be of particular interest to PhD/early career researchers across a wide range of disciplines.

To register your attendance at our seminar, and/or to be added to the LINCS/LINAS Seminar Series Teams space, please email Tomás at tmcinerney01@qub.ac.uk.

The LINCS/LINAS Seminar series is student-led and organised by Dr Meg Schwamb and the doctoral scholars on both programmes. Further information on the doctoral training programmes can be found at the following links:

LINCS (Leverhulme Interdisciplinary Network on Cybersecurity and Society)

LINAS (Leverhulme Interdisciplinary Network on Algorithmic Solutions)