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Astronomy Tea Talk

Monday, May 15, 2023
4:00pm to 5:00pm
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Online and In-Person Event
Mo' Data, No Problem: Into the Age of Industrial Scale Astronomy
Xinlun Cheng, University of Virginia,

With extensive and high precision astronomy databases, new and more sophisticated analysis methods and physics models are necessary. In this talk, I will use three projects to illustrate the necessary changes for industrial scale astronomy. I will present a new discovery and assessment of a well-known phenomenon, Galactic warp, made possible by the large amount ofdata from Gaia. I will examine how traditional analytical methods are holding up with the huge influx of new and high accuracy data in the context of the Kz problem. And lastly, I will showcase how novel techniques in deep learning can be applied into astronomical data mining by using searching for White Dwarf - M dwarf binaries with Gaia stellar spectra as an example.

For more information, please contact Junhan Kim by email at [email protected] or visit

Event Series
Astronomy Tea Talks