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Indian-origin Stanford researcher uses AI to unlock natural hydrogen reserves
Yashee Mathur's startup aims to identify low-cost, low-carbon underground hydrogen using geological data.
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Ankita Baidya - Wed, 08, Jul 2026
- 04:26 EDT
- 29
Yashee Mathur's research combines artificial intelligence and geology to locate naturally occurring hydrogen. / Stanford Graduate School of Business
Indian-origin researcher Yashee Mathur, who completed her PhD in energy sciences engineering at Stanford University in 2026, has developed an artificial intelligence-driven approach to identify naturally occurring underground hydrogen reserves, a potential low-cost, low-carbon energy source.
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Mathur, who was raised near Dhanbad, India's coal capital, said growing up in a region without reliable electricity shaped her interest in expanding access to clean energy.
"I come from a place where we don't have access to electricity 24/7," Mathur told Standford. "The possibility of expanding energy access really resonated with me."
Before pursuing her doctorate at Stanford, Mathur researched geochemistry in Alberta, Canada, and worked as a petrophysicist in India. According to Stanford, she was initially recruited to apply machine learning techniques to oil and gas exploration before expanding her research to carbon capture, geothermal energy and eventually geologic hydrogen, becoming one of the first researchers to specialize in the emerging field.
Also known as "white" hydrogen, naturally occurring geologic hydrogen is increasingly being viewed as an alternative to conventional hydrogen production. Stanford said it offers a middle ground between "grey" hydrogen, produced through steam methane reforming with significant carbon emissions, and "green" hydrogen, generated through electrolysis with near-zero emissions but at relatively high cost.
Furthermore, geologic hydrogen could potentially be extracted for less than $1 per kilogram, making it cheaper than grey hydrogen while producing only a fraction of its carbon emissions.
To advance exploration, Mathur founded Hydrify, a startup that applies artificial intelligence to geological and geophysical datasets, including maps, satellite imagery, soil samples and geologic models, to predict where underground hydrogen deposits are likely to exist.
Stanford also added that the approach differs from traditional exploration methods, which primarily rely on detecting hydrogen seepage at the Earth's surface. Mathur has also filed a patent for a hydrogen detection methodology and completed her doctoral dissertation on the exploration and commercialization of natural hydrogen.
Citing the U.S. Geological Survey, the university noted that even a small portion of Earth's underground hydrogen reserves could contain more energy than all proven natural gas reserves combined, potentially providing enough carbon-free energy for two centuries.
Mathur developed Hydrify with support from several Stanford initiatives, including the Stanford Climate Ventures course, a grant from the Stanford TomKat Center for Sustainable Energy, the Ecopreneurship EcoSprint program and a Stanford Impact Founder fellowship, which enabled her to work on the venture full-time.
Mathur also served as co-president of the Stanford Hydrogen Club during her doctoral studies, while her research was supervised by Tapan Mukerji, co-director of Stanford's Center for Earth Resources Forecasting.
Mathur said the field remains in its early stages but believes the opportunity is significant.
"It could be huge," Mathur told Stanford. "It could also be a geological curiosity. But the potential was too big to ignore."
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