Amir Eskanlou

Postdoctoral Scholar, Earth and Planetary Sciences

Amir is a postdoctoral scholar at Stanford Mineral-X. With 15 years of research and industry experience, his background includes the development and optimization of mineral processing flowsheets for copper, phosphate, graphite and rare earth elements (REEs) from primary and secondary resources. At Stanford, he conducts research related to various aspects of critical minerals processing, including AI-driven reagent discovery, uncertainty quantification, circuit design, and optimization of energy and water consumption.

Education

Ph.D., Penn State, Energy and Mineral Engineering (2024)

Ph.D. Minor, Penn State, Computational Materials Science (2024)

M.S., West Virginia University, Mineral Processing (2021)

M.S., Tarbiat Modares University, Mineral Processing (2016)

B.S., Bahonar University, Mineral Engineering (2013)

Contact

eskanlou@stanford.edu

Mail Code

2115

Links

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Publications

Eskanlou, A., Yin, D. Z., & Caers, J. (2026). Gaussian process regression for modeling computational and experimental mineral processing data. Minerals Engineering. https://doi.org/10.1016/j.mineng.2025.110000