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R1.9m grant for supernova scientist from UWC elected to esteemed science academy

Astrophysicist Dr Michelle Lochner been involved in a few machine-learning papers, led by bright young scientists from around the world, developing and applying machine-learning techniques to detect rare astronomical phenomena. Picture: Supplied

Astrophysicist Dr Michelle Lochner been involved in a few machine-learning papers, led by bright young scientists from around the world, developing and applying machine-learning techniques to detect rare astronomical phenomena. Picture: Supplied

Published Dec 8, 2021

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Astrophysicist Dr Michelle Lochner has received a National Research Foundation, (NRF) P-rating, marking her as one of South Africa’s most promising young researchers.

She’s been elected to the South African Young Academy of Science -- one of only ten scientists honoured this way each year.

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And she’s also been awarded a R1.9m grant to support a PhD student and postdoctoral (postdoc) position working under her on projects related to Chile’s Vera C. Rubin Observatory.

“New telescopes need new techniques. With the next generation of telescopes upon us, my research focus is on rethinking how to do scientific analysis in the era of massive datasets.

“If you have a dataset of one billion galaxies, how would you find the one that would win a Nobel Prize?” she said.

Lochner is a senior lecturer in the department of physics and astronomy at the University of the Western Cape, (UWC) where she works on developing new machine-learning techniques to analyse data and make new scientific discoveries among datasets of millions of astrophysical objects.

These datasets come from telescopes such as MeerKAT and, eventually, the Square Kilometre Array and the Vera C Rubin Observatory’s Large Synoptic Survey Telescope – both under construction.

“These are some of the world’s largest and most powerful scientific tools, powerful enough to probe deeper into space and time than we’ve ever gone before and to help us understand some of the universe’s deepest mysteries... if we have the right scientific techniques to go with it -- and the right people as well,” Lochner said.

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Astrophysicist Dr Michelle Lochner been involved in a few machine-learning papers, led by bright young scientists from around the world, developing and applying machine-learning techniques to detect rare astronomical phenomena. Picture: Supplied

She’s been involved in a few machine-learning papers, led by bright young scientists from around the world, developing and applying machine-learning techniques to detect rare astronomical phenomena.

With UK colleagues, she recently published a paper applying machine learning for the classification of supernovae (exploding stars). In addition, she’s given talks by invitation at a -couple of conferences, including a big machine learning conference at the Astronomical Data Analysis Software and Systems (ADASS) to meet the data science challenges of astronomy -- her first in-person conference in nearly two years.

Lochner is one of a handful of South African Rubin Observatory Principle Investigators (PIs) - a position awarded to scientists outside of the US and Chile to allow them access to Rubin data before it becomes public.

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"The University of the Western Cape is very proud of Dr Lochner's achievements, and happy to see those achievements acknowledged. Dr Lochner embodies the best qualities of any researcher: she works on things that matter, she finds a way to make an impact and, she never forgets that science doesn’t occur in a vacuum -- it’s about people,” said Professor Burtram Fielding, Director of Research at UWC (and upcoming Dean of the Faculty of Natural Sciences).

Cape Argus

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