Publications

Scheidt, C., Neto, F., Yin, D. Z., & Caers, J. (2026). Optimizing Drilling in Brownfield Ni-Cu Depositional Systems Based on the Integration of Geochemical, Geophysical and Drill-Hole Data. Minerals. https://doi.org/10.3390/min16010082

Wei, X., Yin, Z., Bonner, W., & Caers, J. (2026). Falsification of Geological Hypotheses Using Drillholes and Geophysics. Surveys in Geophysics , 1-27. https://doi.org/10.1007/s10712-026-09936-9

Lui, T., Prabhu, A., Bidgood, A., Morrison, S., & Caers, J. (2026). GeoChemNet: An interactive tool for visualizing and interpreting outliers in geochemical data using networks. Applied Geochemistry, 199, 106712. https://doi.org/10.1016/j.apgeochem.2026.106712

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

Xu, W., Eskanlou, A., Arief, M., Yin, D. Z., & Caers, J. (2025). AI-driven optimization under uncertainty for mineral processing operations. Sustainable Earth Resources Communications. https://doi.org/10.46690/serc.2025.02.07

Caers, J. (2025). The future of AI in critical mineral exploration. Sustainable Earth Resources Communications. https://doi.org/10.46690/serc.2025.02.05

Wei, X., Yin, D. Z., Bonner, W., & Caers, J. (2024). Knowledge-driven stochastic modeling of geological geometry features conditioned on drillholes and outcrop contacts. Computers & Geosciences. https://doi.org/10.1016/j.cageo.2024.105779

Mern, J., Corso, A., Burch, D., House, K., & Caers, J. (2024). Intelligent prospector v2.0: exploration drill planning under epistemic model uncertainty. arXiv preprint. https://doi.org/10.48550/arXiv.2410.10610

Scheidt, C., Mathieu, L., Yin, D. Z., Wang, L., & Caers, J. (2024). Masked Autoregressive Flow for Geochemical Anomaly Detection with Application to Li–Cs–Ta Pegmatites Exploration of the Superior Craton, Canada. Natural Resources Research. https://doi.org/10.1007/s11053-024-10409-2

Hall, T. (2023). Efficient Greenfield Mineral Exploration [Stanford University]. https://www.proquest.com/docview/2898143324

Park, S., Tracy, C., & Ewing, R. (2023). Reimagining US rare earth production: Domestic failures and the decline of US rare earth production dominance – Lessons learned and recommendations. Resources Policy, 85, 1-10. https://doi.org/10.1016/j.resourpol.2023.104022

Timbie, . J., Deutch, J., Ellis Jr, . A. J. O. ., Fedor, D., Ewing, R. ., Ram, R., & Park, S. (2023, July 25). Progress On Critical Materials Resilience. Hoover Institution Press.

Moss, R., Corso, A., Caers, J., & Kochenderfer, M. (2023). BetaZero: Belief-State Planning for Long-Horizon POMDPs using Learned Approximations. arXiv preprint.

Wang, L., Yin, Z., & Caers, J. (2023). Data Science for the Geosciences. Cambridge University Press.

Miltenberger, A., Wang, L., Mukerji, T., & Caers, J. (2023). Formulating and Solving the Data-Consistent Geophysical Inverse Problem for Subsurface Modeling Applications. EarthArXiv.

Mern, J., & Caers, J. (2023). Intelligent prospector v1. 0: geoscientific model development and prediction by sequential data acquisition planning with application to mineral exploration. Geoscientific Model Development, 16.

Caers, J. (2023). My journey out of fossil fuel-funded research. Nature Geoscience, 16(6).

Wang, L., Kim, H., Hansen, B., Christiansen, A., Vilhelmsen, T., & Caers, J. (2023). Statistical modeling of three-dimensional redox architecture from non-colocated redox borehole and transient electromagnetic data. Hydrogeology Journal.

Wang, L., Peeters, L., MacKie, E., Yin, D., & Caers, J. (2023). Unraveling the uncertainty of geological interfaces through data-knowledge-driven trend surface analysis. Computers & Geosciences, 178.

Miltenberger, A. (2022). A measure-theoretic approach to Bayesian hypothesis testing and inversion with geophysical data [PhD]. Stanford University.