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Astronomers Find Hyperactive Galaxies in the Early Universe
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By NASA
Research Astrophysicist and Roman’s Deputy Wide Field Instrument Scientist – Goddard Space Flight Center
From a young age, Ami Choi — now a research astrophysicist at NASA — was drawn to the vast and mysterious. By the fifth grade, she had narrowed her sights to two career paths: marine biology or astrophysics.
“I’ve always been interested in exploring big unknown realms, and things that aren’t quite tangible,” Choi said. That curiosity has served her all throughout her career.
In addition to conducting research, Ami Choi shares science with the public at various outreach events, including tours at NASA’s Goddard Space Flight Center in Greenbelt, Md. This photo captures one tour stop, outside the largest clean room at Goddard.Credit: NASA/Travis Wohlrab As a student at University Laboratory High School in Urbana, Illinois, Choi gravitated toward astrophysics and was fascinated by things like black holes. She studied physics as an undergraduate at the University of Chicago, though she says math and physics didn’t necessarily come easily to her.
“I wasn’t very good at it initially, but I really liked the challenge so I stuck with it,” Choi said.
Early opportunities to do research played a pivotal role in guiding her career. As an undergraduate, Choi worked on everything from interacting galaxies to the stuff in between stars in our galaxy, called the interstellar medium. She learned how to code, interpret data, and do spectroscopy, which involves splitting light from cosmic objects into a rainbow of colors to learn about things like their composition.
After college, Choi read an article about physicist Janet Conrad’s neutrino work at Fermilab and was so inspired by Conrad’s enthusiasm and inclusivity that she cold-emailed her to see if there were any positions available in her group.
On October 14, 2023, Ami took a break from a thermal vacuum shift to snap a selfie with a partial eclipse. She was visiting BAE, Inc. in Boulder, Co., where the primary instrument for NASA’s Nancy Grace Roman Space Telescope was undergoing testing. Credit: Courtesy of Ami Choi “That one email led to a year at Fermilab working on neutrino physics,” Choi said.
She went on to earn a doctorate at the University of California, Davis, where she studied weak gravitational lensing — the subtle warping of light by gravity — and used it to explore dark matter, dark energy, and the large-scale structure of the universe.
Her postdoctoral work took Choi first to the University of Edinburgh in Scotland, where she contributed to the Kilo-Degree Survey, and later to The Ohio State University, where she became deeply involved in DES (the Dark Energy Survey) and helped lay the groundwork for the Nancy Grace Roman Space Telescope — NASA’s next flagship astrophysics mission.
“One of my proudest moments came in 2021, when the DES released its third-year cosmology results,” Choi said. “It was a massive team effort conducted during a global pandemic, and I had helped lead as a co-convener of the weak lensing team.”
Choi regularly presents information about NASA’s Nancy Grace Roman Space Telescope to fellow scientists and the public. Here, she gives a Hyperwall talk at an AAS (American Astronomical Society) meeting.Credit: Courtesy of Ami Choi After a one-year stint at the California Institute of Technology in Pasadena, where Choi worked on SPHEREx (Spectro-Photometer for the History of the Universe, Epoch of Reionization and Ices Explorer)—an observatory that’s surveying stars and galaxies—she became a research astrophysicist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. She also serves as the deputy Wide Field Instrument scientist for Roman. Choi operates at the intersection of engineering, calibration, and cosmology, helping translate ground-based testing into flight-ready components that will help Roman reveal large swaths of the universe in high resolution.
“I’m very excited for Roman’s commissioning phase — the first 90 days when the spacecraft will begin transmitting data from orbit,” Choi said.
Choi, photographed here in Death Valley, finds joy in the natural world outside of work. She cycles, hikes, and tends a small vegetable garden with a friend from grad school. Credit: Insook Choi (used with permission) She’s especially drawn to so-called systematics, which are effects that can alter the signals scientists are trying to measure. “People sometimes think of systematics as nuisances, but they’re often telling us something deeply interesting about either the physics of something like a detector or the universe itself,” Choi said. “There’s always something more going on under the surface.”
While she’s eager to learn more about things like dark energy, Choi is also looking forward to seeing all the other ways our understanding of the universe grows. “It’s more than just an end goal,” she said. “It’s about everything we learn along the way. Every challenge we overcome, every detail we uncover, is an important discovery too.”
For those who hope to follow a similar path, Choi encourages staying curious, being persistent, and taking opportunities to get involved in research. And don’t let the tricky subjects scare you away! “You don’t have to be perfect at math or physics right away,” she said. “What matters most is a deep curiosity and the tenacity to keep pushing through.”
By Ashley Balzer
NASA’s Goddard Space Flight Center, Greenbelt, Md.
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Last Updated Sep 09, 2025 EditorAshley BalzerLocationGoddard Space Flight Center Related Terms
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By NASA
5 min read
Astronomers Map Stellar ‘Polka Dots’ Using NASA’s TESS, Kepler
Scientists have devised a new method for mapping the spottiness of distant stars by using observations from NASA missions of orbiting planets crossing their stars’ faces. The model builds on a technique researchers have used for decades to study star spots.
By improving astronomers’ understanding of spotty stars, the new model — called StarryStarryProcess — can help discover more about planetary atmospheres and potential habitability using data from telescopes like NASA’s upcoming Pandora mission.
“Many of the models researchers use to analyze data from exoplanets, or worlds beyond our solar system, assume that stars are uniformly bright disks,” said Sabina Sagynbayeva, a graduate student at Stony Brook University in New York. “But we know just by looking at our own Sun that stars are more complicated than that. Modeling complexity can be difficult, but our approach gives astronomers an idea of how many spots a star might have, where they are located, and how bright or dark they are.”
A paper describing StarryStarryProcess, led by Sagynbayeva, published Monday, August 25, in The Astrophysical Journal.
Watch to learn how a new tool uses data from exoplanets, worlds beyond our solar system, to tell us about their polka-dotted stars.
NASA’s Goddard Space Flight Center
Download images and videos through NASA’s Scientific Visualization Studio.
NASA’s TESS (Transiting Exoplanet Survey Satellite) and now-retired Kepler Space Telescope were designed to identify planets using transits, dips in stellar brightness caused when a planet passes in front of its star.
These measurements reveal how the star’s light varies with time during each transit, and astronomers can arrange them in a plot astronomers call a light curve. Typically, a transit light curve traces a smooth sweep down as the planet starts passing in front of the star’s face. It reaches a minimum brightness when the world is fully in front of the star and then rises smoothly as the planet exits and the transit ends.
By measuring the time between transits, scientists can determine how far the planet lies from its star and estimate its surface temperature. The amount of missing light from the star during a transit can reveal the planet’s size, which can hint at its composition.
Every now and then, though, a planet’s light curve appears more complicated, with smaller dips and peaks added to the main arc. Scientists think these represent dark surface features akin to sunspots seen on our own Sun — star spots.
The Sun’s total number of sunspots varies as it goes through its 11-year solar cycle. Scientists use them to determine and predict the progress of that cycle as well as outbreaks of solar activity that could affect us here on Earth.
Similarly, star spots are cool, dark, temporary patches on a stellar surface whose sizes and numbers change over time. Their variability impacts what astronomers can learn about transiting planets.
Scientists have previously analyzed transit light curves from exoplanets and their host stars to look at the smaller dips and peaks. This helps determine the host star’s properties, such as its overall level of spottiness, inclination angle of the planet’s orbit, the tilt of the star’s spin compared to our line of sight, and other factors. Sagynbayeva’s model uses light curves that include not only transit information, but also the rotation of the star itself to provide even more detailed information about these stellar properties.
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This artist’s concept illustrates the varying brightness of star with a transiting planet and several star spots. NASA’s Goddard Space Flight Center “Knowing more about the star in turn helps us learn even more about the planet, like a feedback loop,” said co-author Brett Morris, a senior software engineer at the Space Telescope Science Institute in Baltimore. “For example, at cool enough temperatures, stars can have water vapor in their atmospheres. If we want to look for water in the atmospheres of planets around those stars — a key indicator of habitability — we better be very sure that we’re not confusing the two.”
To test their model, Sagynbayeva and her team looked at transits from a planet called TOI 3884 b, located around 141 light-years away in the northern constellation Virgo.
Discovered by TESS in 2022, astronomers think the planet is a gas giant about five times bigger than Earth and 32 times its mass.
The StarryStarryProcess analysis suggests that the planet’s cool, dim star — called TOI 3384 — has concentrations of spots at its north pole, which also tips toward Earth so that the planet passes over the pole from our perspective.
Currently, the only available data sets that can be fit by Sagynbayeva’s model are in visible light, which excludes infrared observations taken by NASA’s James Webb Space Telescope. But NASA’s upcoming Pandora mission will benefit from tools like this one. Pandora, a small satellite developed through NASA’s Astrophysics Pioneers Program, will study the atmospheres of exoplanets and the activity of their host stars with long-duration multiwavelength observations. The Pandora mission’s goal is to determine how the properties of a star’s light differs when it passes through a planet’s atmosphere so scientists can better measure those atmospheres using Webb and other missions.
“The TESS satellite has discovered thousands of planets since it launched in 2018,” said Allison Youngblood, TESS project scientist at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “While Pandora will study about 20 worlds, it will advance our ability to pick out which signals come from stars and which come from planets. The more we understand the individual parts of a planetary system, the better we understand the whole — and our own.”
Facebook logo @NASAUniverse @NASAUniverse Instagram logo @NASAUniverse By Jeanette Kazmierczak
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Media Contact:
Alise Fisher
202-358-2546
alise.m.fisher@nasa.gov
NASA Headquarters, Washington
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Last Updated Aug 25, 2025 Related Terms
Astrophysics Exoplanet Atmosphere Exoplanets Galaxies, Stars, & Black Holes Galaxies, Stars, & Black Holes Research Goddard Space Flight Center Kepler / K2 Stars TESS (Transiting Exoplanet Survey Satellite) The Universe View the full article
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By NASA
Sylvie Crowell Credit: NASA Sylvie Crowell, a materials researcher at NASA’s Glenn Research Center in Cleveland, has received a NASA Early Career Initiative (ECI) award for a research proposal titled “Lunar Dust Reduction through Electrostatic Adhesion Mitigation (L-DREAM).” The research focuses on developing a passive lunar dust mitigation coating for solar cells and thermal control surfaces.
Operated under the NASA Space Technology Mission Directorate, the award will fund Crowell’s research in fiscal year 2026, beginning Oct. 1, 2025.
NASA’s ECI is a unique opportunity for the best and brightest of NASA’s early career researchers to lead hands-on technology development projects. The initiative aims to invigorate NASA’s technological base and best practices by partnering early career NASA leaders with external innovators.
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By NASA
Explore This Section Science Uncategorized NASA SCoPE Summer Symposium… Overview Learning Resources Science Activation Teams SME Map Opportunities More Science Activation Stories Citizen Science 4 min read
NASA SCoPE Summer Symposium Celebrates Early Career Scientists and Cross-Team Collaboration
From June 16–18, 2025, the NASA Science Mission Directorate Community of Practice for Education (SCoPE) Summer Symposium brought together a community of scientists, educators, and outreach professionals to celebrate and strengthen NASA’s commitment to developing its workforce and broadening participation in science.
NASA SCoPE is a NASA-funded initiative at Arizona State University that connects early career scientists with NASA Science Activation (SciAct) program teams to build capacity in science communication, community engagement, and educational outreach. Through targeted support like Seed Grants, Travel Grants, and Mission Liaison opportunities, SCoPE equips scientists with the skills and networks needed to meaningfully engage the public with NASA science.
Held in collaboration with key SciAct teams—including Infiniscope, Co-creating with Communities, NASA’s Community College Network, and NASA’s Universe of Learning—the 2025 symposium highlighted the incredible impact of SCoPE over the past four and a half years. The program has financially supported more than 100 early career scientists across a growing network of nearly 1,000 participants.
Over the course of the three-day event, 23 awardees of SCoPE Seed Grants, Travel Grants, and Mission Liaison Grants came together to share their work, connect across disciplines, and explore new avenues for collaboration. Twelve Seed Grant awardees presented their projects, illustrating the transformative power of partnerships with SciAct teams. Highlights included learning how to write for young audiences through mentorship from NASA eClips in support of the children’s book ‘Blai and Zorg Explore the Moon’, designed for elementary learners; a collaborative effort between ‘Lost City, Icy Worlds’ and OpenSpace that evolved into long-term networking and visualization opportunities; and an Antarctic research project that, through collaboration with the Ocean Community Engagement and Awareness using NASA Earth Observations and Science (OCEANOS) project and Infiniscope, both expanded training opportunities for expedition guides and brought polar science to Puerto Rican high school summer interns.
Beyond formal sessions, the symposium embraced community building through shared meals, informal networking, and hands-on experiences like a 3D planetarium show using OpenSpace software, a telescope demonstration with 30 high school students, and a screening of NASA’s Planetary Defenders documentary. Workshop topics addressed the real-world needs of early career professionals, including grant writing, logic model development, and communicating with the media.
Survey responses revealed that 95% of attendees left with a stronger sense of belonging to a community of scientists engaged in outreach. Participants reported making valuable new connections—with peers, mentors, and potential collaborators—and left inspired to try new approaches in their own work, from social media storytelling to designing outreach for hospital patients or other specialized audiences.
As one participant put it, “Seeing others so passionate about Science Communication inspired me to continue doing it in different ways… it feels like the start of a new wave.” Another attendee remarked, “I want to thank the entire team for SCoPE to even exist. It is an incredible team/program/resource and I can’t even imagine the amount of work, dedication and pure passion that has gone into this entire project over the years. Although I only found SCoPE very recently, I feel like it has been incredibly helpful in my scientific journey and I only wish I had learned of the program sooner. Thank you to the entire team for what was a truly educational and inspirational workshop, and the wonderful community that SCoPE has fostered.”
This successful event was made possible through the dedication of NASA SciAct collaborators and the leadership of SciAct Program Manager Lin Chambers, whose continued support of early career engagement through SCoPE has created a growing, connected community of science communicators. The SCoPE Summer Symposium exemplifies how cross-team collaboration and community-centered design can effectively amplify the reach of NASA science.
Learn more about how NASA’s Science Activation program connects NASA science experts, real content, and experiences with community leaders to do science in ways that activate minds and promote deeper understanding of our world and beyond: https://science.nasa.gov/learn/about-science-activation/
SCoPE-funded scientists and collaborators gather at the 2025 SCoPE Summer Symposium to celebrate program success, share ideas, build partnerships, and advance science communication and education efforts across NASA’s Science Activation program. Share
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Last Updated Jul 15, 2025 Editor NASA Science Editorial Team Related Terms
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6 min read
Smarter Searching: NASA AI Makes Science Data Easier to Find
Image snapshot taken from NASA Worldview of NASA’s Global Precipitation Measurement (GPM) mission on March 15, 2025 showing heavy rain across the southeastern U.S. with an overlay of the GCMD Keyword Recommender for Earth Science, Atmosphere, Precipitation, Droplet Size. NASA Worldview Imagine shopping for a new pair of running shoes online. If each seller described them differently—one calling them “sneakers,” another “trainers,” and someone else “footwear for exercise”—you’d quickly feel lost in a sea of mismatched terminology. Fortunately, most online stores use standardized categories and filters, so you can click through a simple path: Women’s > Shoes > Running Shoes—and quickly find what you need.
Now, scale that problem to scientific research. Instead of sneakers, think “aerosol optical depth” or “sea surface temperature.” Instead of a handful of retailers, it is thousands of researchers, instruments, and data providers. Without a common language for describing data, finding relevant Earth science datasets would be like trying to locate a needle in a haystack, blindfolded.
That’s why NASA created the Global Change Master Directory (GCMD), a standardized vocabulary that helps scientists tag their datasets in a consistent and searchable way. But as science evolves, so does the challenge of keeping metadata organized and discoverable.
To meet that challenge, NASA’s Office of Data Science and Informatics (ODSI) at the agency’s Marshall Space Flight Center (MSFC) in Huntsville, Alabama, developed the GCMD Keyword Recommender (GKR): a smart tool designed to help data providers and curators assign the right keywords, automatically.
Smarter Tagging, Accelerated Discovery
The upgraded GKR model isn’t just a technical improvement; it’s a leap forward in how we organize and access scientific knowledge. By automatically recommending precise, standardized keywords, the model reduces the burden on human curators while ensuring metadata quality remains high. This makes it easier for researchers, students, and the public to find exactly the datasets they need.
It also sets the stage for broader applications. The techniques used in GKR, like applying focal loss to rare-label classification problems and adapting pre-trained transformers to specialized domains, can benefit fields well beyond Earth science.
Metadata Matchmaker
The newly upgraded GKR model tackles a massive challenge in information science known as extreme multi-label classification. That’s a mouthful, but the concept is straightforward: Instead of predicting just one label, the model must choose many, sometimes dozens, from a set of thousands. Each dataset may need to be tagged with multiple, nuanced descriptors pulled from a controlled vocabulary.
Think of it like trying to identify all the animals in a photograph. If there’s just a dog, it’s easy. But if there’s a dog, a bird, a raccoon hiding behind a bush, and a unicorn that only shows up in 0.1% of your training photos, the task becomes far more difficult. That’s what GKR is up against: tagging complex datasets with precision, even when examples of some keywords are scarce.
And the problem is only growing. The new version of GKR now considers more than 3,200 keywords, up from about 430 in its earlier iteration. That’s a sevenfold increase in vocabulary complexity, and a major leap in what the model needs to learn and predict.
To handle this scale, the GKR team didn’t just add more data; they built a more capable model from the ground up. At the heart of the upgrade is INDUS, an advanced language model trained on a staggering 66 billion words drawn from scientific literature across disciplines—Earth science, biological sciences, astronomy, and more.
NASA ODSI’s GCMD Keyword Recommender AI model automatically tags scientific datasets with the help of INDUS, a large language model trained on NASA scientific publications across the disciplines of astrophysics, biological and physical sciences, Earth science, heliophysics, and planetary science. NASA “We’re at the frontier of cutting-edge artificial intelligence and machine learning for science,” said Sajil Awale, a member of the NASA ODSI AI team at MSFC. “This problem domain is interesting, and challenging, because it’s an extreme classification problem where the model needs to differentiate even very similar keywords/tags based on small variations of context. It’s exciting to see how we have leveraged INDUS to build this GKR model because it is designed and trained for scientific domains. There are opportunities to improve INDUS for future uses.”
This means that the new GKR isn’t just guessing based on word similarities; it understands the context in which keywords appear. It’s the difference between a model knowing that “precipitation” might relate to weather versus recognizing when it means a climate variable in satellite data.
And while the older model was trained on only 2,000 metadata records, the new version had access to a much richer dataset of more than 43,000 records from NASA’s Common Metadata Repository. That increased exposure helps the model make more accurate predictions.
The Common Metadata Repository is the backend behind the following data search and discovery services:
Earthdata Search International Data Network Learning to Love Rare Words
One of the biggest hurdles in a task like this is class imbalance. Some keywords appear frequently; others might show up just a handful of times. Traditional machine learning approaches, like cross-entropy loss, which was used initially to train the model, tend to favor the easy, common labels, and neglect the rare ones.
To solve this, NASA’s team turned to focal loss, a strategy that reduces the model’s attention to obvious examples and shifts focus toward the harder, underrepresented cases.
The result? A model that performs better across the board, especially on the keywords that matter most to specialists searching for niche datasets.
From Metadata to Mission
Ultimately, science depends not only on collecting data, but on making that data usable and discoverable. The updated GKR tool is a quiet but critical part of that mission. By bringing powerful AI to the task of metadata tagging, it helps ensure that the flood of Earth observation data pouring in from satellites and instruments around the globe doesn’t get lost in translation.
In a world awash with data, tools like GKR help researchers find the signal in the noise and turn information into insight.
Beyond powering GKR, the INDUS large language model is also enabling innovation across other NASA SMD projects. For example, INDUS supports the Science Discovery Engine by helping automate metadata curation and improving the relevancy ranking of search results.The diverse applications reflect INDUS’s growing role as a foundational AI capability for SMD.
The INDUS large language model is funded by the Office of the Chief Science Data Officer within NASA’s Science Mission Directorate at NASA Headquarters in Washington. The Office of the Chief Science Data Officer advances scientific discovery through innovative applications and partnerships in data science, advanced analytics, and artificial intelligence.
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Last Updated Jul 09, 2025 Related Terms
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