Latest news with #RegeneronScienceTalentSearch
BBC News
17-04-2025
- Science
- BBC News
Teenager wins huge cash prize in science competition
An 18-year-old from California, in the US, has won a $250,000 prize (about £188,000) at a prestigious science and mathematics competition for Paz created a powerful AI tool which helped him discover 1.5 million previously unknown variable stars. A variable star is a term used to describe ever-changing astronomical objects such as super massive black holes, volatile newborn stars and supernovas. Matteo's discoveries are thought to be ground-breaking for science and the AI algorithm he created can be used by astronomers all over the world to help make further discoveries. Matteo says he has loved astronomy since he was little and exploring the universe is something he is passionate about. "To be able to contribute in a big way is really special to me," he said after winning the Regeneron Science Talent Search, a national competition run by the US Society for Science."I just feel incredibly blessed," he added. "If I could give one piece of advice to young people with ambition - just start it. You are never going to know before you start where you could go. "Your first step will lead you to your next and that's how you do great things in life." So, what is he going to spend his winnings on? Well, Matteo will probably be quite sensible with it as in his spare time, he runs a project which helps teach school-age children about financial basics and money only that, but he loves music and even owns a concert promotion business. What did Matteo's work help discover? Matteo studied information from Nasa's Wide-field Infrared Survey Explorer (WISE) mission. The project launched in 2009 and has been scanning the skies for astronomical bodies ever since. When the infrared telescope discovers a change in light, it pinpoints an interesting astronomical object such as a black hole or another galaxy. With over 15 years worth of data from the WISE telescope, Matteo knew studying the whole lot manually would take way too long, so he came up with an AI algorithm to search the data for new anomalies. His work helped him catalogue 1.9 million objects, over 1.5 million of which are potential new, undiscovered objects.
Yahoo
15-04-2025
- Science
- Yahoo
High Schooler Uncovers 1.5 Million Hidden Objects in Space, Wins $250K
High school student Matteo Paz has stunned the scientific community by identifying 1.5 million previously unknown objects in space. By creating an artificial intelligence algorithm, Paz found a way to sift through vast amounts of space data and uncover millions of cosmic objects hiding in plain sight. His work didn't just impress scientists; it earned him the top prize at the 2025 Regeneron Science Talent Search — a $250,000 award that goes to the most promising young scientists in the U.S. It all started during Caltech's Planet Finder Academy in 2022. The summer outreach program is designed to give high schoolers hands-on experience in astronomy, and Paz was hooked. The following year, he signed up for a six-week Caltech program that pairs students with campus mentors. Paz was assigned to Davy Kirkpatrick. "The first day I talked to him, I said that I was considering working on a paper to come out of this, which is a much larger goal than six weeks," said Paz. "He didn't discourage me. He said, 'OK, so let's talk about that.' He has allowed an unbridled learning experience. I think that's why I've grown so much as a scientist.' With encouragement from Kirkpatrick, Paz tasked himself with a daunting challenge: How do you process and make sense of nearly 200 terabytes of space data gathered by NASA's NEOWISE (Near-Earth Object Wide-field Infrared Survey Explorer) telescope? NEOWISE has been scanning the sky for asteroids for over a decade. At the same time, it has captured data on other variable objects. According to Caltech, these are 'hard-to-catch phenomena like quasars, exploding stars, and paired stars eclipsing each other.' The NASA telescope was able to detect the varying heat of these objects, but the sheer size of the dataset made it impossible for human astronomers to comb through them. With almost 200 billion rows of data, going through it by hand was never an option, and Paz never considered it. The 18-year-old had a knack for AI, coding, and computer science. Combining this with his substantial math knowledge (he has been studying advanced undergraduate math for the last few years), he created an AI model to sift through the data for him. In the short six-week program, he began using machine learning to make an AI model that could recognize patterns in the infrared data — subtle signals that might indicate the presence of cosmic objects. Kirkpatrick acted as an astronomy consultant and helped him interpret the data. The duo kept working on the project after the six weeks were up. By 2024, Paz was mentoring other high school students on the subject. Now the model can tear through the raw data from the NEOWISE telescope. They have made a jaw-dropping 1.5 million discoveries, each a potential new clue about the structure and history of our universe. Since winning the 2025 Regeneron Science Talent Search, Paz hasn't slowed down. He and Kirkpatrick hope to publish the complete catalog of newly found objects this year. Paz has also secured his first paid job. He is working at Caltech, continuing his research and collaborating with astrophysicists on how to scale his AI system for even bigger projects.
Forbes
08-04-2025
- Science
- Forbes
Teen Wins $250,000 For Discovering 1.5 Million New Space Objects
An 18-year-old student from Pasadena, California, placed first in the nation's oldest and most prestigious science and mathematics competition for high school students, winning $250,000. Matteo Paz was one of the finalists who submitted an original research science project in this year's Regeneron Science Talent Search. The students represented 39 schools across 16 states and the finalists competed for nearly $2 million in prizes and awards. Paz's project analyzed a massive amount of astronomical data collected by NASA's WISE explorer telecope. Using an algorithm he developed, he sorted through the information and identified over a million new celestial objects in the night sky. 'Congratulations to the winners of this year's Regeneron Science Talent Search,' said Maya Ajmera, President and CEO, Society for Science and Executive Publisher, Science News. 'The remarkable creativity and dedication of these students bring renewed hope for our future. Driven by their ingenuity, these young scientists are developing groundbreaking solutions that have the potential to transform our world and propel society forward.' Winning first place was a shock to Paz, who had no expectations after being named a finalist. 'I was just happy to have had the privilege. Not only placing in the top 10, but winning first place, came as a visceral surprise. It still hasn't fully sunk in,' remarked Paz. The path to victory was not without its trials, as earlier this year, he and his family had been evacuated from their home in Pasadena due to the Eaton Fire. During the project's development, he faced challenges in the code or quirks within the data itself. Fortunately, Paz found the process of refining algorithms, and mathematical complexities deeply engaging. As he looked through the primary results, he began seeing unique and unstudied objects. "What's exciting is that some variable phenomena I'm detecting don't have obvious explanations. These quirky, mysterious objects are exactly those that spark new science and physics," remarked Paz. Launched in 2009, NASA's Wide-Field Infrared Survey Explorer (WISE) collected 200 billion lines of infrared astronomical data (200 terabytes). However, this data had not been cataloged. In his Regeneron Science Talent Search project, Matteo Paz developed waveform-based machine learning methods to detect and characterize variables within the data. These methods included a machine-learning algorithm dubbed VARnet. Paz developed VARnet to detect variable objects specifically by combining machine learning with particular mathematical concepts. The first mathematical operation served to de-noise data while conserving short-timescale variation. The second operation, which Paz calls the Finite-Embedding Fourier Transform, serves to extract patterns in the data. Working together, these operations resulted in the identification of 1.9 million infrared variable objects, including 1.5 million new discoveries. Among those discoveries are objects like supermassive black holes, newborn stars, and supernovae. Matteo Paz first place research poster at the 2025 Regeneron Science Talent Search. The first ... More complete infrared variability survey - detection and classification of 1.9 million objects Listen to Paz explain his project in his own words Learn more about Matteo Paz here. After wrapping up the VarWISE project, Paz would like to continue his work in astronomy. He believes that, by using the discoveries from his project, we could properly measure the rate of expansion of the universe and challenge our understanding of its origin. However, he feels that finding funding over the next few years may prove difficult. To learn more about all of this year's top 40 finalists, visit the Society for Science.
Yahoo
14-03-2025
- Health
- Yahoo
North Carolina teen inspired by Native American roots wins national science prize
A teenager from North Carolina says her pride in her Native American culture helped inspire the research that was just recognized for a national science prize. WTVD reports Ava Grace Cummings of Johnston County won a six-figure prize after placing 2nd in the 2025 Regeneron Science Talent Search. Cummings won the prize for her research on Native American myopathy, also known as the muscle disorder stac3. WTVD spoke with the teen, and she said it was a subject that was close to her. 'Just bringing more resources and more advocacy and more awareness to medicine within these areas. I was able to contribute to that by looking at this disease that's specific to my tribe and also using our traditional practices and finding a solution,' Cummings told WTVD. CHECK IT OUT >> Charlotte high school student wins scholarship for designing homes meant to weather rising seas According to WTVD, Cummings tested adult flies and larvae for her research. She combined an experimental amyotrophic lateral sclerosis (ALS) drug called Tirasemtiv with a nettle herb and found that the pair improved movement. She told WTVD she's a member of the Lumbee and Coharie tribes. 'One of the approaches I used in my project was bridging western medicine and also traditional indigenous practices,' she told WTVD. Cummings says she was accepted into Yale University and hopes to major in bio-medical engineering. WTVD reports the $175,000 she won from the talent search will go towards her college tuition. (VIDEO: How local students got to visit Jimmy Carter at the White House in the 1970s)
Yahoo
13-03-2025
- Science
- Yahoo
An 18-year-old won $250,000 for discovering over a million objects in space. Some could help unravel one of the universe's biggest mysteries
High schooler Matteo Paz won $250,000 for discovering 1.5 million new space objects with AI. Paz built an AI algorithm to search data from a NASA space telescope for objects like black holes. His discoveries could help solve one of the universe's biggest mysteries. When Matteo Paz scored a high school internship at the California Institute of Technology, the scientists there gave him the daunting task of manually sorting reams of data from a NASA mission. It was "classic intern work," Paz, an 18-year-old from Pasadena, California, told Business Insider. "The very menial, tedious, dirty tasks that require a lot of time." Instead of manually sifting through the data, Paz built an AI algorithm to do it for him. Ultimately, he discovered 1.5 million new objects in space, including supernovae and supermassive black holes. On Tuesday, he won $250,000 in the Regeneron Science Talent Search for his efforts. Every year the competition casts a net across the nation for high schoolers doing the type of research you might expect from graduate students. This year Paz snagged first place out of nearly 2,500 entrants. "Surprised isn't a strong enough word," Paz said shortly after the award ceremony. "I didn't even give a thought to what I'd say to people if I'd won." The objects in Paz's catalog aren't just plain old stars or planets. They're all variable objects, meaning they change dramatically, violently, and often unpredictably. A black hole, for example, can emit powerful jets that vary in brightness depending on how much material it's gobbling up or how fast it's spinning. That makes these objects a wealth of information about some of the universe's most befuddling mysteries. For example, they can be used to measure how quickly the universe is expanding from the Big Bang — a puzzle scientists are still trying to solve, which could rewrite physics. Most of the objects Paz discovered are "candidates," meaning further study is required for scientists to confirm what Paz's analysis suggests they are. Luckily, astronomers are already digging into his catalog. Paz needed his machine-learning algorithm to comb through nearly 200 terabytes of data from a 10-year infrared survey of the entire sky by NASA's NEOWISE space telescope. Looking in the infrared — wavelengths invisible to the human eye — the NEOWISE mission searched for asteroids and comets near Eart. Infrared wavelengths, however, can also reveal objects deep in space that are shrouded in interstellar dust. Even though NEOWISE wasn't designed to look for such objects, Paz thought he could tease them out of the data with his AI algorithm. "Prior to Matteo's work, no one had tried to use the entire (200-billion-row) table to identify and classify all of the significant variability that was there," Davy Kirkpatrick, who was Paz's mentor at Caltech, told BI in an email. Other surveys had tried to comb through NEOWISE data for specific types of variable objects, he added. At the end of the summer program, "we were so impressed with his results that we hired him part-time at Caltech to finish the catalog," Kirkpatrick said. Paz said a lot of that work was him "in a dark room, eye bags heavy, looking at my computer, trying to solve a bug." Sometimes he worked out math problems on a whiteboard at Caltech. He also consulted a variety of astrophysicists and astronomers. Once the algorithm was ready though, it blew him away. In order to analyze all 200 terabytes of data, Paz divided up the data into 13,000 equal parts. The algorithm analyzed miniscule changes in infrared radiation to identify variable space objects and sort them into different classes, such as black holes or double-star systems. In some constellations, the algorithm was discovering more objects than anticipated. "That was where I first started to see a lot of promise in the project," Paz said. In the end, he surveyed over 450 million objects in the sky and identified 1.9 million that may be variable objects like black holes or supernovae. Of those, 1.5 million had never been cataloged before — they were new discoveries. "It's very beautiful. Not just that number — it's a big number that obviously makes you proud — but when you visualize the data," Paz said. Here's that visualization, plotting all the candidate objects he discovered: "You can see the Milky Way, you can see satellite galaxies, you can see Andromeda, you can see star-forming regions," Paz said. "Even though it's a very one-dimensional view of the universe, just plotting a point at every discovery we've made, we can really see the intricacies and the glory of the night sky." Now an infrared research group at Caltech is already using his catalog, called VarWISE, to study dual-star systems in the distant universe. They've already found dozens of star systems in VarWISE that weren't previously detected, Kirkpatrick said. He added that the research helps them calculate the mass of distant alien planets. Paz is submitting the catalog for publication in the Astrophysical Journal later this year. The catalog has not yet gone through the peer-review process, but the algorithm itself was peer-reviewed and published in the Astronomical Journal in November. "The variable candidates that he's uncovered will be widely studied and illustrate the enduring value of astronomical surveys," Amy Mainzer, a scientist who led the NEOWISE mission, told BI in an email. "It's clear that he is simply a unique talent — smart, hardworking, and with a crazy ability to assimilate newfound knowledge into new ideas for studying the universe," Kirkpatrick said. As for Paz and his $250,000, the next frontier is college. He said he's been accepted at Stanford University, and is keeping his mind open about potential career paths. Just weeks before flying to Washington, DC for the awards ceremony, Paz woke up in his Pasadena home to see flames outside the window. The Eaton fire traveled so quickly that he had received no official warning. After evacuations and several days of fire, his family's home was spared. "It really gives you a new perspective," he said. "I have a new appreciation for the problems that I have the privilege not to worry about." Now he's pondering the possibility of putting an infrared telescope into Earth orbit — this time to monitor Earth itself for emerging fires. More immediately, though, Paz wants to use his NEOWISE findings to study the elusive expansion rate of the universe, starting from the Big Bang, and hopefully help scientists solve the biggest mystery in cosmology. "It will either contribute to the resolution of a very contentious topic in current research, or it's going to reveal something truly foundational about the origins of the universe," Paz said. Read the original article on Business Insider
