AI Among the Stars: How Machines Help Us Explore the Universe
Feb
25
2026
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Arya Farahi -
Niall Gaffney -
Stella Offner -
Josh Taylor
Feb
25
2026
-
Arya Farahi
-
Niall Gaffney
-
Stella Offner
-
Josh Taylor
Description
The recent revolution in artificial intelligence (AI), together with technical advances in telescopes and computing, have opened new frontiers for astronomy data processing and analysis.
Meanwhile, open, rich, massive datasets are the lifeblood of AI innovation. In the current big-data era of astronomy, new facilities like the Vera C. Rubin Observatory are generating a firehose of new data. Planned facility upgrades, like the next-generation Very Large Array (ngVLA) and Atacama Large Millimeter Array (ALMA), will routinely yield datasets containing 1 trillion voxels, exceeding current processing capacity and requiring fresh AI developments.
Panelists will discuss:
- How AI tools will interact with current and forthcoming surveys to accelerate astronomy research workflows;
- Highlight recent AI applications for analysis of big datasets;
- Discuss the activities of the NSF-Simons AI Institute for Cosmic Origins (CosmicAI), an institute at UT Austin aiming to develop transformative AI approaches to tackle astronomy problems.
About the Speakers
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Arya Farahi
Assistant Professor
Department of Statistics and Data Sciences, UT Austin
Arya Farahi is the director of the D3 Lab, which is dedicated to advancing knowledge and innovation in statistical sciences, AI, astronomy and decision-making. Farahi is a co-PI and working ...
Arya Farahi is the director of the D3 Lab, which is dedicated to advancing knowledge and innovation in statistical sciences, AI, astronomy and decision-making. Farahi is a co-PI and working group lead at the NSF-Simons AI Institute for Cosmic Origins, based at UT Austin. His research focuses on understanding the unexpected and not-well-understood consequences of AI models, including algorithmic bias and uncertainty quantification, and developing cutting-edge methodologies and tools to mitigate these challenges.
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Niall Gaffney
Director of Computing
Texas Advanced Computing Center (TACC)
Niall Gaffney's background primarily focuses on the management and use of large, inhomogeneous scientific datasets. He earned his B.A., M.A. and Ph.D. degrees in astronomy from The University of Texas ...
Niall Gaffney's background primarily focuses on the management and use of large, inhomogeneous scientific datasets. He earned his B.A., M.A. and Ph.D. degrees in astronomy from The University of Texas at Austin and joined TACC in May 2013. Most of his focus has been on creating environments to foster better data practices, including improving metadata, data processing, analysis and reuse. He focuses on improving researchers' data practices to accelerate outcomes and better feed machine learning and artificial intelligence applications, which are increasingly adopted across science and engineering research. Much of this stems from his 13 years as a designer and developer for the archives at the Space Telescope Science Institute (STScI), which holds the data from the Hubble Space Telescope, Kepler, and James Webb Space Telescope missions.
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Stella Offner
Professor
Department of Astronomy, UT Austin
Stella Offner's research focuses on understanding how stars like our Sun form. She performs computer simulations of the turbulent birth environment of stars and uses them to predict what telescopes ...
Stella Offner's research focuses on understanding how stars like our Sun form. She performs computer simulations of the turbulent birth environment of stars and uses them to predict what telescopes will observe: synthetic observations. This work has broader implications for the evolution of galaxies and the initial conditions of planetary systems. Offner is the director of the NSF-Simons AI Institute for Cosmic Origins. She is a core faculty member in the Oden Institute for Computational Engineering and Sciences and co-director of the Center for Scientific Machine Learning. She is also a member of the Center for Planetary Systems Habitability and the Machine Learning Laboratory.
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Josh Taylor
Research Associate
UT Austin Oden Institute and CosmicAI Institute
Joshua J. Taylor is a postdoctoral fellow in the Department of Astronomy at The University of Texas at Austin, a member of the Scientific Machine Learning group at the Oden ...
Joshua J. Taylor is a postdoctoral fellow in the Department of Astronomy at The University of Texas at Austin, a member of the Scientific Machine Learning group at the Oden Institute for Computational Engineering and Sciences and part of the Observable Universe initiative within CosmicAI. His research advances unsupervised machine learning methods for unbiased, data-driven exploratory and summary analysis of astrophysical data, particularly data from observations and simulations of the star formation process. Taylor received his Ph.D. in statistics from Rice University.
Location
Peter O'Donnell Building, Avaya Auditorium, Room 2.302
201 E. 24th Street
Parking: San Jacinto Garage