Taking AI to the Stars

From February 23-25, the National Science Foundation AI Planning Institute for Data-Driven Discovery in Physics held “AI Super-Resolution Simulations: From Climate Change to Cosmology,” a hybrid conference showcasing artificial intelligence-assisted research across a myriad of disciplines. 

Along with researchers from Carnegie Mellon University, the conference invited people from Japan, Iran and other nations to join. About 50 scientists were able to attend in person with 150 more attending online.

“The main idea was to just bring people in different disciplines together in a way that we hadn't really done before to such an extent,” said Rupert Croft, professor of physics and member of the McWilliams Center for Cosmology, who helped organize the event. “CMU is interdisciplinary, and so we just noticed that people share a common language and now that common language is artificial intelligence. I think the most exciting thing was just to get these different communities together and everyone realized that they could actually understand each other.”

Because of this universal language, participants were able to understand each other’s research, even when it did not fall under their disciplines. 

“There were people there who study distant galaxies, climate change, blood flow in the heart, racecar engines and urban planning, all linked by a common thread — the use of AI to speed up computer modeling of physics by factors of thousands,” said Croft.

Pedram Hassanzadeh, assistant professor of mechanical engineering at Rice University and Earth, environmental and planetary sciences, attended and spoke at the conference. He appreciated the interdisciplinarity of the conference, and he is excited for the potential of AI in his own research.

“I think there is a lot for these disciplines to learn from each other on using AI for their specific applications,” said Hassanzadeh. “Super-resolution is critical for a broad range of applications in fluid mechanics and climate science. The approach can be used, for example, to better account for small-scale process in climate models for climate change projections, or to provide more details on wind power availability for renewable energy forecasting.”

CMU graduate students were also able to get involved. Yueying Ni, a physics Ph.D. candidate, gave an in-person talk on “Super-Resolution Cosmological Simulations,” where she talked about how she was able to use AI to discover where celestial bodies are based on the surrounding dark matter.

Croft was excited to have graduate students participating in the conference.

“We noticed that a lot of graduate student applicants have worked on AI in their undergraduate research and careers, and they want to continue using those techniques now,” said Croft. “Many of our keynote speakers were graduate students who were enthusiastic. There were even first year graduate students who gave great talks, so that's maybe a little bit different to usual conferences.”

Croft is hoping that these events can continue in the future with funding from the NSF. He hopes that other researchers can understand the potential of AI in their fields.

“We'd like to expand the range of what we're doing, or we'd just like to hold events like this one,” said Croft. “We think that AI is going to become a part of physics in the way that experiments are, and pencil and paper are.”