Hassan Talebi

Research Scientist in Geospatial Data Analytics and Geostatistics

As a geoscience data analyst, I have extensive research experience in geo-modelling, including mineral potential mapping, mineral resource evaluation, spatial uncertainty modelling and risk assessment, spatial data integration, geostatistics, and machine learning.

Geoscience data are typically mixed and high-dimensional with complex statistical and spatial relationships. The focus of my research is to develop new predictive models to address the complexity of geoscience data and to improve the geoscience process discovery analyses.


Technical skills

  • Mineral exploration
  • Geostatistical modelling
  • Machine learning for spatial data integration
  • Spatial uncertainty modelling and risk assessment


Professional experience

September 2018 – present
Research Scientist: CSIRO Deep Earth Imaging Future Science Platform, Australia

March 2019 – present
Adjunct Lecturer: School of Science, Edith Cowan University, Australia

November 2017
Research Intern: Helmholtz Institute Freiberg for Resource Technology, Germany

April 2017 – September 2017
Research Intern: BHP Billiton, Australia

April 2016
Research Intern: Helmholtz Institute Freiberg for Resource Technology, Germany



PhD (Geostatistics) EdithCowan University, Australia (2018)

MSc (Mining Engineering – Geostatistics) University of Tehran, Iran (2013)

BSc (Mineral exploration), University of Birjand, Iran (2010)


Selected publications

Talebi, H., Peeters, L. J. M., Mueller, U., Tolosana-Delgado, R., & van den Boogaart, K. G. 2020. Towards geostatistical learning for the geosciences: A case study in improving the spatial awareness of spectral clustering. Mathematical Geosciences52, 1035-1048.

Talebi, H., Mueller, U., Tolosana-Delgado, R., 2019. Joint simulation of compositional and categorical data via direct sampling technique – Application to improve mineral resource confidence, Computers & Geosciences, Volume 122, pp 87-102.

Talebi, H., Mueller, U., Tolosana-Delgado, R., van den Boogaart, K. G., 2019. Geostatistical simulation of geochemical compositions in the presence of multiple geological units – Application to mineral resource evaluation, Mathematical Geosciences, Volume 51, Issue 2, pp 129–153.

Talebi, H., Mueller, U., Tolosana-Delgado, R., Grunsky, E.C., McKinley, J.M., Caritat, P.de., 2019. Surficial and deep earth material prediction from geochemical compositions, Natural Resources Research, Volume 28, Issue 3, pp 869–891

Talebi, H., Lo, J., Mueller, U., 2017. A hybrid model for joint simulation of high-dimensional continuous and categorical variables. In: J.J. Gómez-Hernández, J. Rodrigo-Ilarri, M.E. Rodrigo-Clavero, E. Cassiraga and J.A. Vargas-Guzmán (Editors), Geostatistics Valencia 2016. Springer International Publishing, Cham, pp. 415-430.

Talebi, H., Hosseinzadeh Sabeti, E., Azadi, M., Emery, X., 2016. Risk quantification with combined use of lithological and grade simulations: Application to a porphyry copper deposit, Ore Geology Reviews, Volume 75, pp 42-51.

Talebi, H., Asghari, O., Emery, X., 2015. Stochastic rock type modelling in a porphyry copper deposit and its application to copper grade evaluation, Journal of Geochemical Exploration, Volume 157, pp 162-168.

Talebi, H., Asghari, O., Emery, X., 2014. Simulation of lately injected dykes in an Iranian Porphyry copper deposit using the Plurigaussian model. Arabian Journal of Geoscience, Volume 7, Issue 7, pp 2771-2780.

Talebi, H., Asghari, O., Emery, X., 2013. Application of the Plurigaussian simulation to delineate the layout of alteration domains in Sungun copper deposit, Central European Journal of Geosciences, Volume 5, Issue 4, pp.514-522.