Latest news with #MatteoPaz
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
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
Yahoo
12-03-2025
- Science
- Yahoo
Regeneron Science Talent Search 2025 Awards More Than $1.8 Million to High School Seniors for Innovative Research on Classifying Celestial Objects, Treating a Rare Muscle Disease and Solving a Long-Standing Math Problem
$250,000 top award goes to Matteo Paz in America's longest running and most distinguished science and math competition TARRYTOWN, N.Y. and WASHINGTON, March 11, 2025 /PRNewswire/ -- Regeneron Pharmaceuticals, Inc. and Society for Science (the Society) announced that Matteo Paz, 18, of Pasadena, California, won the top award of $250,000 in the 2025 Regeneron Science Talent Search, the U.S.'s oldest and most prestigious science and math competition for high school seniors. Now in its 84th year, the competition celebrates and rewards young innovators who are applying their Science, Technology, Engineering and Math (STEM) talent and leadership skills to push the boundaries of discovery and address today's pressing challenges. Forty finalists, including Matteo, were honored this evening during an award ceremony at the National Building Museum in Washington, D.C, where they were awarded more than $1.8 million in prizes for their groundbreaking research, exceptional problem-solving skills and potential to shape the future of STEM. Matteo Paz, 18, of Pasadena, California, won first place and $250,000 for designing machine-learning algorithms to efficiently comb through 200 billion entries of raw NEOWISE infrared full-sky data. By analyzing tiny changes in infrared radiation, the AI sorted the objects into 10 classes. He found 1.5 million new potential objects. Second place and $175,000 went to Ava Grace Cummings, 18, of Smithfield, North Carolina, for creating a fruit fly model of STAC3 disorder, or Native American myopathy (a rare genetic muscle disease). She found that the common nettle herb, alone or combined with the experimental drug Tirasemtiv, improved movement in both adult flies and larvae. Third place and $150,000 went to Owen Jianwen Zhang, 18, of Bellevue, Washington, who solved a long-standing math problem about objects called 3-uniform hypergraphs. He proved a maximum value for how many 3-uniform hypergraphs can have similar structures but differing connections. Owen's results have applications in computer science. "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." The Regeneron Science Talent Search provides a national platform for high school seniors to showcase original, innovative STEM research that proposes novel solutions to real-world issues. Finalists are evaluated for their scientific rigor, originality, critical thinking, leadership potential and commitment to drive meaningful impact across crucial STEM fields. "The Science Talent Search changed my life. At my high school, STS winners were treated like star athletes, and I never imagined I would belong in such an amazing group of kids who were operating at a whole different level than I had ever seen," said George D. Yancopoulos, co-Founder, Board co-Chair, President and Chief Scientific Officer of Regeneron and a 1976 Science Talent Search finalist and top winner. "The experience of competing in STS and being named a top winner gave me the confidence to devote my life to science. So, congratulations to this year's finalists and winners, you are America's best and brightest. I hope this moment inspires you to push boundaries, challenge assumptions and use your brilliance to change the world." Other top honors from the competition include: Fourth Place: Logan Lee, 18, of Honolulu, Hawaii received a $100,000 award for helping sterile male mosquitoes survive in the wild. These males are important in mosquito control. Logan improved their survival by giving them a transplant of wild mosquito bacteria. His transplant helped the sterile mosquitoes grow faster and survive better in the wild. Fifth Place: Rivka Lipkovitz, 18, of San Francisco, California received a $90,000 award for using statistical modeling to study U.S. voter ID laws. She found that presidential election turnout dropped by 2.4% in states that passed strict laws after 2008. Turnout for midterm elections increased. Knowing how laws affect turnout can help shape future policies. Sixth Place: Melody Heeju Hong, 17, of Wantagh, New York received a $80,000 award for developing a powerful, flexible statistical model for mapping sites called trans-methylation quantitative trait loci (trans-mQTL) within the human genome. These sites are key to understanding the interplay between genes and environment in disease and aging. Seventh Place: Kevin Shen, 18, of Olympia, Washington received a $70,000 award for building a custom flight computer to control a 3D-printed airplane with oblique wings. These aircraft can be more fuel-efficient but are hard to control. His oblique-wing aircraft and flight computer improved flight efficiency by 9.2%. Eighth Place: Minghao Zou, 18, of Santa Clara, California received a $60,000 award for simulating protons to probe environments that produce subatomic particles called neutrinos. He created an algorithm mimicking extreme astrophysical conditions, such as electromagnetic and gravitational forces and interactions with nearby particles. He verified it using known cases of particle motion. Ninth Place: Thanush Patlolla, 17, of Cary, North Carolina received a $50,000 award for approximating the density of electrons using a finite nuclear model. Using a mathematical strategy called a density function, he created a model to map electrons in a nuclear simulation. The map increased the accuracy of energy distribution predictions by 0.6%. Tenth Place: Ray Zhang, 17, of Chantilly, Virginia received a $40,000 award for studying how to better treat drug-resistant Fusarium fungal infections. Ray studied how the fungus builds sticky communities of cells that resist drug treatment. He also found that using a combination of drugs better controlled the fungus. Akilan Sankaran, 17, of Albuquerque, New Mexico was named the Seaborg Award winner and selected to speak on behalf of the Regeneron Science Talent Search Class of 2025. The 40 finalists chose Akilan as the student who best exemplifies their class and the legacy of nuclear chemist Glenn T. Seaborg, who won the Nobel Prize for Chemistry in 1951 and served on the Society's Board of Trustees for 30 years. All other finalists received $25,000. All 40 finalists join a distinguished group of Science Talent Search alumni, many of whom have gone on to achieve world-changing careers in STEM, with some earning esteemed honors, including the Nobel Prize, National Medal of Science, and MacArthur Fellowship. In total, Regeneron awarded $3.1 million in prizes, including $2,000 to each top scholar and their school. Learn more about Regeneron Science Talent Search at and learn about all their research projects at our Virtual Public Showcase. For media resources, visit About Society for Science Society for Science is a champion for science, dedicated to promoting the understanding and appreciation of science and the vital role it plays in human advancement. Established in 1921, Society for Science is best known for its award-winning journalism through Science News and Science News Explores, its world-class science research competitions for students, including the Regeneron Science Talent Search, the Regeneron International Science and Engineering Fair and the Thermo Fisher Scientific Junior Innovators Challenge, and its outreach and equity programming that seeks to ensure that all students have an opportunity to pursue a career in STEM. A 501(c)(3) membership organization, Society for Science is committed to inform, educate and inspire. Learn more at and follow us on Facebook, Twitter, Instagram and Snapchat (Society4Science). About Regeneron Regeneron (NASDAQ: REGN) is a leading biotechnology company that invents, develops and commercializes life-transforming medicines for people with serious diseases. Founded and led by physician-scientists, our unique ability to repeatedly and consistently translate science into medicine has led to numerous approved treatments and product candidates in development, most of which were homegrown in our laboratories. Our medicines and pipeline are designed to help patients with eye diseases, allergic and inflammatory diseases, cancer, cardiovascular and metabolic diseases, hematologic conditions, infectious diseases and rare diseases. Regeneron believes that operating as a good corporate citizen is crucial to delivering on our mission. We approach corporate responsibility with three goals in mind: to improve the lives of people with serious disease, to foster a culture of integrity and excellence and to build sustainable communities. Regeneron is proud to be included on the Dow Jones Sustainability World Index and the Civic 50 list of the most "community-minded" companies in the U.S. Throughout the year, Regeneron empowers and supports employees to give back through our volunteering, pro-bono and matching gift programs. Our most significant philanthropic commitments are in the area of science education, including the Regeneron Science Talent Search and the Regeneron International Science and Engineering Fair (ISEF). For more information, please visit or follow Regeneron on LinkedIn, Instagram, Facebook or X. Media ContactsJoseph Brown, Regeneron386-283-1323, Gayle Kansagor, Society for Science703-489-1131, gkansagor@ View original content to download multimedia: SOURCE Society for Science
