
Studying a galaxy far, far away could become easier with help from AI, says researcher
CBC20-07-2025
A recent Memorial University of Newfoundland graduate says his research may help study galaxies more efficiently — with help from Artificial Intelligence.
As part of Youssef Zaazou's master's of science, he developed an AI-based image-processing technique that generates predictions of what certain galaxies may look like in a given wavelength of light.
"Think of it as translating galaxy images across different wavelengths of light," Zaazou told CBC News over email.
He did this by researching past methods for similar tasks, adapting current AI tools for his specific purposes, finding and curating the right dataset to train the models, along with plenty of trial and error.
"Instead of … having to look at an entire region of sky, we can get predictions for certain regions and figure out, 'Oh this might be interesting to look at,'" said Zaazou. "So we can then prioritize how we use our telescope resources."
Zaazou recently teamed up with his supervisors Terrence Tricco and Alex Bihlo to co-author a paper on his research in The Astrophysical Journal, which is published by The American Astronomical Society.
Tricco says this research could also help justify allocation of high-demand telescopes like the Hubble Space Telescope, which has a competitive process to assign its use.
A future for AI in astronomy
Both Tricco and Zaazou emphasised the research does not use AI to replace current methods but to augment them.
Tricco says that Zaazou's findings have the potential to help guide future telescope development, and predict what astronomers might expect to see, making for more efficient exploration.
Calling The Astrophysical Journal the "gold standard" for astronomy journals in the world, Tricco hopes the wider astronomical community will take notice of Zaazou's findings.
"We want to have them be aware of this because as I was mentioning, AI, machine learning, and physics, astronomy, it's still very new for physicists and for astronomers, and they're a little bit hesitant about these tools," said Tricco.
Tricco praised the growing presence of space research in general at Memorial University.
"We are here, we're doing great research," he said.
He added growing AI expertise is also transferable to other disciplines.
"I think that builds into our just tech ecosystem here as well."
'Only the beginning'
Though Zaazou's time as a Memorial University student is over, he hopes to see research in this area continue to grow.
"I'm hoping this is the beginning of further research to be done," he said.
Though Zaazou described his contribution to the field as merely a "pebble," he's happy to have been able to do his part.
"I'm an astronomer. And it just feels great to be able to say that and to be able to have that little contribution because I just love the field and I'm fascinated by everything out there," said Zaazou.
As part of Youssef Zaazou's master's of science, he developed an AI-based image-processing technique that generates predictions of what certain galaxies may look like in a given wavelength of light.
"Think of it as translating galaxy images across different wavelengths of light," Zaazou told CBC News over email.
He did this by researching past methods for similar tasks, adapting current AI tools for his specific purposes, finding and curating the right dataset to train the models, along with plenty of trial and error.
"Instead of … having to look at an entire region of sky, we can get predictions for certain regions and figure out, 'Oh this might be interesting to look at,'" said Zaazou. "So we can then prioritize how we use our telescope resources."
Zaazou recently teamed up with his supervisors Terrence Tricco and Alex Bihlo to co-author a paper on his research in The Astrophysical Journal, which is published by The American Astronomical Society.
Tricco says this research could also help justify allocation of high-demand telescopes like the Hubble Space Telescope, which has a competitive process to assign its use.
A future for AI in astronomy
Both Tricco and Zaazou emphasised the research does not use AI to replace current methods but to augment them.
Tricco says that Zaazou's findings have the potential to help guide future telescope development, and predict what astronomers might expect to see, making for more efficient exploration.
Calling The Astrophysical Journal the "gold standard" for astronomy journals in the world, Tricco hopes the wider astronomical community will take notice of Zaazou's findings.
"We want to have them be aware of this because as I was mentioning, AI, machine learning, and physics, astronomy, it's still very new for physicists and for astronomers, and they're a little bit hesitant about these tools," said Tricco.
Tricco praised the growing presence of space research in general at Memorial University.
"We are here, we're doing great research," he said.
He added growing AI expertise is also transferable to other disciplines.
"I think that builds into our just tech ecosystem here as well."
'Only the beginning'
Though Zaazou's time as a Memorial University student is over, he hopes to see research in this area continue to grow.
"I'm hoping this is the beginning of further research to be done," he said.
Though Zaazou described his contribution to the field as merely a "pebble," he's happy to have been able to do his part.
"I'm an astronomer. And it just feels great to be able to say that and to be able to have that little contribution because I just love the field and I'm fascinated by everything out there," said Zaazou.
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