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California student wins $40K for physics research

By Sohail Khan 20 August 2026, 8:10 pm

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Business News›News›International›Global Trends›18-year-old California student Seth Jacob Nabat wins $40,000 in prestigious Regeneron science competition for machine-learning program that could help physicists better understand particle collisions

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18-year-old California student Seth Jacob Nabat wins $40,000 in prestigious Regeneron science competition for machine-learning program that could help physicists better understand particle collisions

Synopsis

Eighteen-year-old California student Seth Jacob Nabat has won $40,000 after placing 10th in the 2026 Regeneron Science Talent Search. His innovative machine-learning project is designed to help physicists analyse high-energy particle collisions and better understand how symmetry breaks in complex experimental data. Seth also teaches classrooms of elementary and middle school students college-level mathematics.

An 18-year-old California high school student Seth Jacob Nabat has earned national recognition for developing a machine-learning system designed to help physicists better understand what happens when high-energy particles collide. Seth Jacob Nabat, a senior at William Howard Taft Charter High School in Woodland Hills, California, secured 10th place in the 2026 Regeneron Science Talent Search (Regeneron STS) for his research project on particle physics.

The achievement came with a $40,000 award. According to the Society for Science, Nabat developed his project to tackle a difficult problem in analysing particle-collision data.

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Seth Nabat's breakthrough in particle physics

Nabat's project, titled “Learning Broken Symmetries With Approximate Invariance To Better Classify Particle Collision Events,” uses machine learning to analyse the results of high-energy particle collisions.

Physicists rely on computer models to study these collisions. However, models that assume symmetrical outcomes can save computing time and energy while also creating the risk of doubling certain measurement errors.

Nabat designed a three-part machine-learning system to address the problem.

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The first network “knows” about symmetry and uses that knowledge to efficiently approximate the results of particle collisions. A second, unconstrained network identifies camera and measurement errors, while a third network looks for patterns in those errors.

In testing, the combined model was able to work with imperfect data without giving up the efficiency benefits of the symmetry-based approach.

The significance of Nabat's work goes beyond simply making calculations faster. His model allows researchers to examine what actually causes symmetry to break. This is a fundamental issue in physics, particularly in quantum field theory.

That makes the project notable because machine learning is increasingly being explored as a tool for handling the enormous amounts of complex data generated by modern physics experiments.

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More than a science competition winner

Nabat's interests also extend beyond his research. At William Howard Taft Charter High School, he is a co-captain of the varsity debate team, giving him experience in argumentation and public speaking.

He also volunteers with the UCLA Math Circle, where he teaches elementary and middle school students advanced mathematics and assists other instructors with their classes.

His combination of scientific research, mathematics, teaching and debate highlights the broader range of interests behind his achievement.

A surprisingly funny moment

Despite his impressive academic accomplishments, Nabat has also had his share of unexpected adventures. According to his Society for Science profile, the first time he rode a mule during a family trip, the animal became frightened by a deer carcass and bucked him off.

It is an amusing contrast to the highly technical work that earned him a place among the country's top young science researchers.

The Regeneron Science Talent Search has a long history of recognising outstanding high school researchers in science, mathematics and related fields. For Nabat, the $40,000 prize is recognition of research that could contribute to the way scientists process and interpret complicated particle-collision data.

His achievement also offers a glimpse of how young researchers are increasingly combining artificial intelligence, machine learning and fundamental science to tackle problems that have challenged scientists for decades.

At just 18, Seth Nabat has already made his mark in one of America's most prestigious high school science competitions, and his research could be an early indication of where the next generation of physics and AI research is headed.

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