For four years, the computer scientist Trieu Trinh has been consumed with something of a meta-math problem: how to build an A.I. model that solves geometry problems from the International Mathematical Olympiad, the annual competition for the world’s most mathematically attuned high-school students.

Last week Dr. Trinh successfully defended his doctoral dissertation on this topic at New York University; this week, he described the result of his labors in the journal Nature. Named AlphaGeometry, the system solves Olympiad geometry problems at nearly the level of a human gold medalist.

While developing the project, Dr. Trinh pitched it to two research scientists at Google, and they brought him on as a resident from 2021 to 2023. AlphaGeometry joins Google DeepMind’s fleet of A.I. systems, which have become known for tackling grand challenges. Perhaps most famously, AlphaZero, a deep-learning algorithm, conquered chess in 2017. Math is a harder problem, as the number of possible paths toward a solution is sometimes infinite; chess is always finite.

“I kept running into dead ends, going down the wrong path,” said Dr. Trinh, the lead author and driving force of the project.