Gloria Quispe Oruro
PhD student Stanford University
Gloria is a PhD student in the Earth and Planetary Sciences at Stanford University, specializing in critical minerals exploration and mining development. Her current research focuses on understanding how subsurface heterogeneity controls groundwater flow and pressure evolution in deep copper deposits. She applies advanced computational approaches, including 3D geologic modeling, Monte Carlo simulation, uncertainty quantification, and DGSA sensitivity analysis, to develop a high-resolution hydrogeologic model of the Mingomba Cu deposit in Zambia in collaboration with KoBold Metals and Stanford Mineral-X. Her work aims to improve the prediction of pressure responses during mining development and dewatering planning, ultimately contributing to safer and more efficient extraction strategies. Gloria’s professional background in mining spans geotechnical engineering, mine geology, and responsible mining initiatives. She has worked with Newmont and Sibanye-Stillwater, conducting highwall stability analyses, structural mapping, rock-mass characterization, and predictive modeling. She has also contributed to NSF-funded Responsible Mining & Resilient Communities projects in Peru and Colombia, focusing on water access, artisanal mining, and social-impact frameworks. She aims to advance data-driven, socially grounded exploration and mine-planning frameworks that improve critical-mineral projects globally.
2026 Agenda Sessions
AI-based optimisation of exploration, mining and mineral processing
This conversation begins with a look at AI-based prospect generation, where algorithms are now capable of synthesising geological data with economic viability, environmental constraints, and social impact models to identify targets that are not only rich in minerals but also feasible and responsible to develop.
Wednesday 11 February 16:10 - 17:10 Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall)
Disruptive technologies
This conversation begins with a look at AI-based prospect generation, where algorithms are now capable of synthesising geological data with economic viability, environmental constraints, and social impact models to identify targets that are not only rich in minerals but also feasible and responsible to develop.
Nubian Pyramids Stage (CTICC2 - Ground Floor - Exhibition Hall) Africa/Johannesburg








-Logo_CMYK_1.jpg?width=1000&height=500&ext=.jpg)













_1.png?ext=.png)




























_mi25-weblogo.png?ext=.png)


