Meet the AAS Keynote Speakers: Dr Stella Offner

In this series of posts, we sit down with a few keynote speakers of the 245th AAS meeting to learn more about them and their research. You can see a full schedule of their talks here and read our other interviews here!


Background

A picture of Dr. Stella Offner, who is a blonde woman in her 40s.

Her journey into astronomy started through physics and math, and while in graduate school at UC Berkeley, she became interested in solving problems through scientific computing. “I could have gone in any particular route, but when I looked into astrophysics, it seemed like the physics, particularly the physics of star formation, was really interesting and diverse,” she said. “Especially because you have magnetic fields and radiation and gravity and turbulence, and astrochemistry. So there’s really a lot to work with; it’s very rich.”

After graduate school, Dr. Offner became a NASA Hubble Fellow at Yale, followed by a position as an NSF Postdoctoral Fellow at the Harvard-Smithsonian Center for Astrophysics. She then took a post as an Assistant Professor at the University of Massachusetts Amherst, before finally becoming an Associate Professor at UT Austin, where she works today.

Current Research

Dr. Offner’s current work can be summarized into two distinct parts. Firstly, we have her actual hard science research: studying the foundational physics of star formation. “In my group, we basically try to understand how the different mechanisms of stellar feedback (outflows, winds, supernovae radiation, etc…) impact star cluster formation.” She said. “I’ve been recently working with my students a lot on adding in brand new physics, such as non-ideal magnetohydrodynamics and cosmic ray transport, to the whole star cluster formation process. So there’s been a strong focus on both of these processes on star cluster formation. All of this is done on classical high-performance computing astrophysics research.” This kind of research is incredibly important as it helps answer some of the most basic questions about star formation, like for example, why do some stars end up in binaries and others not? “We have no theories whatsoever for that. We can do lots of simulations. And so that is a super interesting problem, which I continue to be interested in. I mean, it’s so simple.” Said Dr. Offner. “Just, like, count the number of stars in the system and explain why you have that number of stars. And yet it’s so hard.”

However, when she’s not uncovering the fundamental reasons why stars exist, Dr. Offner is working as the director of a new NSF-funded institute: the AI Institute for Cosmic Origins (CosmicAI) . This is a collaboration whose goal is to develop AI tools that astronomers can use to manage the upcoming petabytes of data from surveys like LSST/Rubin, SDSS-V, and the Roman Space Telescope. On the research side, CosmicAI is focused on four “grand challenge” problems:

  1. Helping astronomers search, model, and explore data through the use of large language learning models.
  2. Preparing for the next generation of big data that’s coming out from upgraded facilities like the VLA, ALMA, and the aforementioned surveys.
  3. Simulation-based inference, or in other words, how can we use explainable AI techniques to infer things about underlying physical parameters? This particular group is mainly focused on cosmology and dark matter.
  4. Speeding up simulations using AI techniques. This group is focused on using astrochemistry as a testbed to develop models that can overcome computational bottlenecks.

Beyond just research, she was also enthusiastic about the educational and community aspects of CosmicAI. “We have programs for professional level, undergraduate level, and sort of, you know, high school and general public. So at the highest level, for broader impacts, we’re organizing seminars and conferences, like just as community research, things like that. We’re also going to be releasing all of our tools and softwares and making a data platform. So this will help enable people to curate data, develop models, and run them on big datasets and astronomy.” said Dr. Offner. “We also want the community to have better fluency in AI practices. We’re doing AI Astro boot camps, and at the undergraduate level, we’re launching summer and winter schools to train undergrads in data analysis and coding plus AI applications.”

Advice for Early-Career Astronomers

Thinking back to her undergrad and grad school experience, Dr. Offner had the following to say:

“It’s really hard. You do have to kind of love what you do and have some grit and some confidence that you can succeed. I would say speak up, networking and collaboration is a super important part of doing research. And I think the more, engaging and fun research is, the more it helps you weather those ups and downs, particularly the downs.”

To learn more about simulations of the physics of star clusters, and the future of AI in astronomy, be sure to attend Dr. Stella Offner’s Plenary Lecture: The Star Formation Engine at 8:00 am EST on Thursday, January 16th at #AAS245!


Edited by: Sowkhya Shanbhog

Featured Image Credit: AAS

Author

  • Amaya Sinha

    I’m a 4th year graduate student at the University of Utah. I’m a galactic archeologist, and my specific research focus involves using stellar populations within the Milky Way to study its chemical and dynamical history!

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