Creating solutions for the mining industry


Our key competences.

Research + Technology

We combine the expertise of our multidisciplinary team to push forward the mining industry with innovative and fresh ideas.


Modelling in mining is about Big Data. We successfully tackle this by fine tuning algorithms to run on small and powerful hardware.


We have pioneered in the region the technology transfer from the university to our industrial partners.


Some of our most recent work


Alges Library for Creative Image Analysis


Geostatistical Software Library


Software for geometric restitution of geological ore bodies


These are our latest publications.

  1. Cárdenas, E., Townley, B., Ortiz, J., & Kracht, W. (2014). Geochemical quantitative mineral characterization for geometallurgical applications in porphyry copper deposits.
  2. Rezaee, H., Asghari, O., Koneshloo, M., & Ortiz, J. M. (2014). Multiple-Point Geostatistical Simulation of Dykes: Application at Sungun Porphyry Copper System, Iran. Stochastic Environmental Research and Risk Assessment, 1–15.
  3. Peredo, O., Ortiz, J. M., & Leuangthong, O. (2014). Inverse modeling of moving average kernels for 3D Gaussian simulation. Paris, France.
  4. Peredo, O., Ortiz, J. M., Herrero, J. R., & Samaniego, C. (2014). Tuning and Hybrid Parallelization of a Genetic-based Multi-Point Statistics Simulation Code. Parallel Computing, 40(5), 144–158.
  5. Peredo, O., & Ortiz, J. M. (2014). Resurrecting GSLIB by code optimization and multi-core programming. In Geostatistical and geospatial approaches for the characterization of natural resources in the environment: Challenges, Processes and Strategies. New Dehli, India.
  6. Pérez, C., Mariethoz, G., & Ortiz, J. M. (2014). Verifying the high-order consistency of training images with data for multiple-point geostatistics. Computers &Amp; Geosciences, 70, 190–205.
  7. Lois, P., Kracht, W., Townley, B., & Ortiz, J. (2014). Water/rock interactions and physicochemical controls on mineral processing: being predictive based on geology.
  8. Ortiz, J. M. (2014). Geometallurgical Modelling and Mine Planning, CSIRO Chile Program 2.
  9. J.M., O. (2014). Challenges in analysis of geo-metallurgical data: Linking numbers with interpretations.
  10. Ortiz, J. M., & Magri, E. J. (2014). Designing and Advanced RC Drilling Grid for Short-Term Planning in Open Pit Mines: Three Case Studies. The Journal of the Southern African Institute of Mining and Metallurgy, 114(8), 631–639.
  11. Lois, P., Townley, B., Kracht, W., & Ortiz, J. M. (2013). Physicochemical modeling of the behavior of different mineralogical units in milling and flotation.
  12. Gutiérrez, R., Ortiz, J. M., & Townley, B. (2013). Categorical variables simulation incorporating local varying anisotropy.
  13. Soto, F., Ortiz, J. M., Herreros, D., & Valencia, M. (2013). Geometric restitution for improving mineral resource estimation applied to Peumo deposit.

Meet Our Team

The people who make our solutions work for you.

Antonio Barberán


Álvaro Egaña


Carlos González


Daniel Baeza


Felipe Navarro


Fabian Soto


Julián M. Ortiz


Mauricio Garrido

Master Student

Óscar Peredo


Industrial & Scientific Partners

The people we work with.