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  • Jiayin Dong
    Coming home: Jiayin Dong joins Illinois Astronomy faculty
    Jiayin Dong
    Illinois astronomy professor Jiayin Dong

    When Jiayin Dong walks across the University of Illinois campus this fall, it will feel familiar and entirely new.

    Dong, an incoming assistant professor in the Department of Astronomy, is returning to Illinois as a faculty member, where she earned her undergraduate degrees in Engineering Physics and Astronomy. Previously a Flatiron Research Fellow at the Center for Computational Astrophysics in New York, Dong brought a passion for understanding how planetary systems form and evolve, and a deep affection for the university where she first looked through a telescope.

    Dong’s path to astronomy wasn’t set from day one. “I began as a general studies major,” she recalls. “I spent my first year just exploring different courses—physics, astronomy, philosophy, engineering.” But an impromptu encounter changed everything. “One day, I walked by the observatory, and my roommate told me you could take a one-credit class. I did that and used the telescope to see the sky for the first time. Seeing pictures is much different than seeing it through the eyepiece.”

    That sense of discovery stuck with her. During her undergraduate years, Dong worked on research with Professor Leslie Looney, analyzing protoplanetary disks. “It was pretty cool because I was the first person to see those images,” she says.

    After graduating from Illinois, Dong pursued her PhD in Astronomy & Astrophysics at Penn State under the guidance of Bekki Dawson. At the Flatiron Institute, she combined computational models, statistical analysis, and dynamical theory to study how planetary systems form—and why they look so different from what scientists once expected.

    “Before the discovery of exoplanets, we thought our understanding of planets was complete,” Dong explains. “That all changed in 1995 when the first exoplanet was discovered—a giant planet orbiting very close to its host star. It was completely different from our solar system.” The discovery opened up an entirely new field of study. “Now we need a new picture to describe planet formation. That’s why it’s exciting—you’re making discoveries and pushing the theory forward.”

    Some of the biggest questions in the field are the ones that first drew her in. “What is the physical process that drives the diversity of exoplanet systems? What is a typical solar system? Is ours unique, or just one example of a broader range of systems?” Dong asks. New missions on the horizon, such as GAIA Data Release 4, promise to expand our understanding. “In the past, we’ve mostly mapped out inner planets. GAIA will tell us about planets with orbital distances beyond a few astronomical units. We don’t know what we’ll find—maybe we’ll have another discovery moment.”

    Returning to Illinois, Dong is eager to contribute to this fast-moving field and to help raise the university’s profile in exoplanet research. “It’s nice to bring my expertise and connections to Illinois,” she says. “I’m excited about the opportunity. Illinois is a place where I know the department and the campus pretty well. It feels like a safe place—a home.”

    She also looks forward to mentoring and guiding students along the path she once walked. “I’ve been talking to students and faculty, and I feel the real transition—the much larger responsibility of teaching that younger version of me.” Her advice to current undergraduates? “Explore broadly. Take classes outside of your major. For me, philosophy and geology courses helped me figure out my interests. Undergrad is one of the best times to explore.”

    When she’s not analyzing planetary systems, Dong enjoys more down-to-earth hobbies. “I like milk tea a lot. I explore a lot of coffee places. I also really like watching and playing ice hockey.”

    Now, as she returns to Illinois—this time at the front of the classroom—Dong brings her cutting-edge expertise and the enthusiasm and curiosity that drew her to the stars through the observatory eyepiece. And she’s eager to help the next generation of Illinois students discover that same sense of wonder.

  • Decker
    A rising star in astronomy and mentorship

    When Decker French learned she had been named a Lincoln Excellence for Assistant Professors Scholar, it was a complete surprise.

    “I didn’t know that I was nominated,” she said. “So it was a very pleasant surprise! It is incredibly rewarding to have this kind of recognition for work that’s been evolving since I first joined the department.”

    Decker
    Professor Decker French was named a Lincoln Excellence for Assistant Professors Scholar.

    The LEAP Scholar award is one of the campus’s most competitive honors for early-career faculty. For French, who joined the Department of Astronomy in 2020, the timing felt especially meaningful: “This is the phase where I can see meaningful results come together from my group’s work over the last five years.”

    French’s research focuses on how galaxies form, change, and—eventually—stop forming stars. In particular, she studies violent cosmic events known as tidal disruption events, or TDEs. “I study what happens when stars get ripped apart by black holes to study extreme gravity,” she said. “It’s one of the few ways we can really learn about black holes that would otherwise be invisible. From these measurements, we aim to learn how supermassive black holes first formed and how they grow in concert with their host galaxies.”

    These rare events, which produce a sudden flare as stellar debris falls into a black hole, offer a powerful way to study how galaxies evolve. French’s multi-wavelength approach combines optical, radio, and submillimeter data—and increasingly, machine learning tools—to trace these processes across space and time.

    An environment for discovery

    Before coming to Illinois, French received her bachelor’s degrees from MIT and her PhD from the University of Arizona. After school, she was a Hubble Postdoctoral Fellow at the Carnegie Observatories in Pasadena, California, where she studied galaxy evolution using multi-wavelength observations. French joined the department because she was drawn to its depth, methods, and collaborative spirit. “The department was engaged in a broad range of innovative and impactful science,” she said. “I saw an opportunity not only to contribute meaningfully, but also to grow by learning from colleagues with diverse expertise. That combination was really compelling.”

    She now works closely with faculty across specialties and sees students participate in multiple research collaborations—a dynamic she believes benefits everyone involved. “I think students can really benefit from learning from multiple mentors,” she said. “When students have access to a wide range of skills and areas of expertise, it benefits them and results in great science.”

    French also teaches Astro 406, a hands-on course that introduces students to how scientific research works in practice. “Knowing how that works is an extremely useful skill,” she said.

    As her lab continues to grow, she’s primarily focused on one enduring question: What causes galaxies to stop forming stars? “We think that one of the key places we get energy to do this is from the black hole,” she explained. “In principle, that’s enough energy to change the galaxy—but in practice, it’s tricky to catch that happening in action.”

    French has found a new passion in Illinois when she’s not probing the secrets of distant galaxies. “Since moving here, I’ve gotten really into sailing,” she said. “There’s a group out at Clinton Lake that sails pretty regularly.”

    As her research advances and her students take on increasingly ambitious projects, French’s work continues to bridge discovery and mentorship—shaping our understanding of the cosmos and the people who will study it next.

  • Headshot
    Unlocking the cosmos with AI

    It began with a problem of scale. 

    Modern telescopes like the Vera C. Rubin Observatory, set to begin operations in October 2025, are poised to revolutionize astronomy by capturing unprecedented volumes of data—millions of time-variable astrophysical events across the sky each night. But with this scale comes a new challenge: How do you process, classify, and interpret this firehose of information when human analysis alone can’t keep up with the hundreds of new events being reported by Rubin every second? 

    That’s the frontier being navigated by Gautham Narayan, professor of astronomy at the University of Illinois and deputy director for astrophysics research at the NSF-Simons AI Institute for the Sky (SkAI). His group has spent over a decade pioneering artificial intelligence in astrophysics, developing early classification and inference algorithms, and helping lay the groundwork for a supercharged field by SkAI. “My group has been doing AI and astrophysics for about the last decade,” Narayan explains. “SkAI is a way to take the things I've been doing locally here at Illinois, and really make it a much larger effort that is multi-institute.” 

    Founded to harness the parallel revolutions in AI and astronomy, the SkAI Institute is working toward what Narayan calls “foundation models for astronomy.” These are AI models inspired by systems like ChatGPT but tailored to the complexities of “multi-modal” astrophysical data—images, spectra, and time series. If applied at scale, these models could be transformative. “If you could do classification, forecasting, inference, and analysis now at an industrial scale for billions of objects in a year,” he says, “that has the potential to change everything we know about astrophysics.” 

    A powerful example of this potential came with GW170817—the first observed merger of two neutron stars. Astronomers detected the event across multiple wavelengths and combined data from observatories worldwide to form a multidimensional view of the explosion and the origins of heavy elements. “What was valuable was seeing how combining data from all of these telescopes could give you such a multidimensional view,” Narayan recalls. “The obvious question is, well, what if you could do that for 100,000 objects?” 

    That’s where AI steps in—not just as a tool for managing data at scale but as an engine for discovery. 

    A mission at the intersection

    SkAI’s mission is to marry astronomy and AI in a scientifically rigorous and fundamentally interpretable way. “We care about our model’s predictive power,” Narayan emphasizes, “and making sure our models are interpretable, that a human can look at what an AI algorithm has done and say, ‘Yes, this makes physical sense.’” 

    The Institute’s reach is broad and collaborative, with partner institutions including Northwestern, the University of Illinois, the University of Chicago, the Adler Planetarium, Fermilab, Argonne National Lab, and community colleges like Parkland in Champaign. Cultural institutions such as the Spurlock and Krannert Art museums on campus are also involved, broadening the impact beyond traditional scientific spaces. 

    Education and outreach are key pillars of SkAI’s vision. Students at Illinois whose work aligns with the Institute’s priorities can receive funding, and the same opportunities extend to postdoctoral fellows, including through a unique preceptorship program. “We also have opportunities for postdocs,” Narayan notes, “including a preceptor postdoctoral fellow who has to be engaged in education and outreach work in the community colleges.” 

    Rethinking astronomy education and infrastructure

    Looking ahead, Narayan envisions a research environment where scientists interact with powerful AI tools not by writing specialized code but through intuitive, natural-language queries. “You could ask it: ‘Can you find me 100 low-redshift spiral galaxies in Rubin images with space-based Euclid images that also show stellar streams?’” he says. “Something that would have taken a grad student a year, you could potentially do in seconds.” 

    This shift could significantly reshape how educators teach astronomy. “I think in the long term, we are going to have to revise our astronomy curriculum to embed AI into almost every class we offer,” Narayan predicts. 

    The ripple effects extend well beyond university classrooms. Through efforts like SCiMMA (Scalable Cyberinfrastructure for Multi-Messenger Astrophysics), Narayan and his collaborators are bridging siloed observatories nationwide, building a national infrastructure where telescopes and AI systems work in concert. “SCiMMA’s mission is to connect all of these things,” he explains, “so that ultimately you can build this AI-enabled future that I’ve been trying to describe.” 

    What’s next?

    Narayan is building a foundation model for time series data, especially for explosive events like supernovae and kilonovae. The goal is to move beyond simply classifying these events to analyzing them at scale—studying their physical properties, distributions, host environments, and behaviors as a population. “That’s a hard task because nobody’s done it systematically yet,” he says. “It’s hard to assemble the data and develop methods that combine data from different facilities with traditional non-AI techniques. But I want to get to the point where we can essentially ask these AI models for a large sample and analyze them all at once.” 

    In parallel, he continues work on projects like the Rubin Observatory, the Young Supernova Experiment, and SCiMMA—all feeding into SkAI’s broader mission of building an AI-powered ecosystem for astronomy. “I think you’ll see a revolutionary change in how we deal with data, not just doing what we do now at a larger scale, but asking entirely new questions that we couldn’t have asked before,” he adds.