Math Colloquium: Anomaly Detection in Astronomical Data using Machine Learning

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sms colloquium michelle lochner

Anomaly Detection in Astronomical Data using Machine Learning

Dr. Michelle Lochner
Senior Lecturer
University of the Western Cape
South African Radio Astronomy Observatory

Register Here for Zoom Link


Abstract
:

The next generation of telescopes such as the 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, I 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.

Speaker Bio:
Born in South Africa with a PhD from the University of Cape Town, Dr. Michelle Lochner is a Senior Lecturer with a joint position between the University of the Western Cape and the South African Radio Astronomy Observatory (formally SKA South Africa). Her focus is on cosmology and trying to get the best out of combining optical and radio telescopes like the Rubin Observatory and the Square Kilometre Array. She works on developing new statistical techniques and using machine learning to tackle the masses of data we are dealing with in astronomy, currently focusing on the use of anomaly detection for scientific discovery. She is also the director of an international mentoring programme for women in physics called the Supernova Foundation (www.supernovafoundation.org).

Intended Audience:
All are welcome. Those with interest in the topic.
 


Contact
Yosef Zlochower
Event Snapshot
When and Where
November 04, 2020
1:25 pm - 2:15 pm
Room/Location: See Zoom Registration Link
Who

This is an RIT Only Event

Interpreter Requested?

No

Topics
research