Indian-origin sixth-grader trains machine-learning model to spot lithium deposits with 89% accuracy

Ishaan Dokania, the Indian-origin Beaverton sixth-grader (Image Credit: Society for Science) A sixth-grade student from Oregon is using satellite images and machine learning to explore a problem that is becoming increasingly important as demand for lithium grows. Ishaan Dokania, a sixth-grader at Willamette Valley Academy in Beaverton, is among the 30 finalists in the 2026 Thermo Fisher Scientific Junior Innovators Challenge. According to the Society for Science, Ishaan developed a project called “Eye in the Sky: From Pixels to Predictions for Lithium and Beyond”, using satellite imagery and geological data to train a machine-learning model that could identify potential lithium deposits. After addressing sources of noise in the data, his model detected lithium deposits with 89% accuracy.How Ishaan connected satellite images with mineral explorationIshaan's project began with two interests that might initially seem unrelated: remote sensing and rocks and minerals. While participating in a Science Olympiad competition, he studied both subjects and began thinking about whether they could be combined to solve a practical problem. That question led him to lithium exploration.Lithium is ...