Felipe Santibañez-Leal

Felipe Santibañez-Leal

he/him

I&F Decision Science Assoc. Manager @ Accenture | Applied Scientific Researcher

Publications

You can also find my articles on my Google Scholar profile.

Journal Articles

HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy

Published in Scientific Data (Nature), 2023

A publicly available hyperspectral image database for supervised analysis in geometallurgy, enabling reproducible research in mineral characterization from spectral data.

Recommended citation: Santibañez-Leal, F.A., Ehrenfeld, A., Garrido, F., Navarro, F., & Egaña, A. (2023). "HIDSAG: Hyperspectral Image Database for Supervised Analysis in Geometallurgy." Scientific Data, 10, 167.
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A Robust Stochastic Approach to Mineral Hyperspectral Analysis for Geometallurgy

Published in Minerals, 2020

This work summarizes the research carried out for the characterization of geometallurgical samples, through the use of signal and image processing tools, with the use of hyperspectral data.

Recommended citation: Alvaro F. Egaña, Felipe A. Santibáñez-Leal, Christian Vidal, Gonzalo Díaz, Sergio Liberman, and Alejandro Ehrenfeld. (2020). "A Robust Stochastic Approach to Mineral Hyperspectral Analysis for Geometallurgy." Minerals, Special Issue: Advanced Spectral Techniques for Mineralogical and Elemental Analysis in Mining and Mineral Processing. Online first.
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Ore-Waste Discrimination with Adaptive Sampling Strategy

Published in Natural Resources Research, 2020

In this paper, a method to select sampling locations is proposed in an advanced drilling grid for short-term planning and grade control in order to improve the correct assessment (ore-waste discrimination) of blocks.

Recommended citation: Felipe A. Santibáñez-Leal, Julián M. Ortiz, and Jorge F. Silva. (2020). "Ore-Waste Discrimination with Adaptive Sampling Strategy." Natural Resources Research. 29. pp 3079 - 3102
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Geological Facies Recovery Based on Weighted ℓ1-Regularization

Published in Mathematical Geosciences, 2019

A weighted compressed sensing (WCS) algorithm is proposed for the problem of channelized facies reconstruction from pixel-based measurements.

Recommended citation: Hernan Calderon, Felipe Santibañez, Jorge F. Silva, Julián M. Ortiz, and Alvaro Egaña. (2015). "Geological Facies Recovery Based on Weighted ℓ1-Regularization." Mathematical Geosciences. 52. pp 593 - 617.
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Sampling Strategies for Uncertainty Reduction in Categorical Random Fields: Formulation, Mathematical Analysis and Application to Multiple-Point Simulations

Published in Mathematical Geosciences, 2019

The task of optimal sampling for the statistical simulation of a discrete random field is addressed from the perspective of minimizing the posterior uncertainty of non-sensed positions given the information of the sensed positions.

Recommended citation: Felipe Santibañez, Jorge F. Silva, and Julián M. Ortiz. (2019). "Sampling Strategies for Uncertainty Reduction in Categorical Random Fields: Formulation, Mathematical Analysis and Application to Multiple-Point Simulations." Mathematical Geosciences . 51. pp 579 - 624
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Computational methods for analysis of dynamic events in cell migration

Published in Current Molecular Medicine, 2014

Image processing approaches for quantitative description of cell migration in 2- and 3-dimensional image series, including registration, segmentation, shape and topology description, tracking and motion fields are presented. We discuss advantages, limitations and suitability for different approaches and levels of description.

Recommended citation: Castañeda V, Cerda M, Santibáñez F, Jara J, Pulgar E, Palma K, Lemus CG, Osorio-Reich M, Concha ML, Härtel S. (2014). "Computational methods for analysis of dynamic events in cell migration." Current Molecular Medicine. 14(2). PMID: 24467201.
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Conference Papers

Geometallurgical estimation of mineral samples from hyperspectral images and topic modelling

Published in 18 International Conference on Mineral Processing and Geometallurgy, 2022

The problem of characterizing the spatial-spectral variability of mineral samples is formalized as a topic modelling task, a central technique from the field of natural language processing.

Recommended citation: Felipe A. Santibáñez-Leal, Alejandro Ehrenfeld, Felipe Garrido, Felipe Navarro and Álvaro Egaña (2022). Geometallurgical estimation of mineral samples from hyperspectral images and topic modelling. 18 International Conference on Mineral Processing and Geometallurgy, Sept 2022.
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Analysis of seismic tomography and geological data to identifying spatial relationships between large ore deposits in northern Chile using machine learning methods: Preliminary results

Published in AGU Fall Meeting, 2021

This work shows that machine learning techniques are useful to understand the spatial relationships between large porphyry copper deposits within other data sources towards mineral exploration.

Recommended citation: Comte, D., “Analysis of seismic tomography and geological data to identifying spatial relationships between large ore deposits in northern Chile using machine learning methods: Preliminary results”, vol. 2021, Art. no. H35M-1172, 2021.
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Multi Pixel Stochastic Approach to Mineral Samples Spectral Analysis for Geometallurgical Modeling

Published in Procemin Geomet, 2020

This work proposes a novel approach for analysis of spectra data for the mining industry, that uses multi pixel hyperspectral images and statistical analysis techniques to overcome the effects of ambient conditions and geological context variability to estimate critical geological and geometallurgical interest variables.

Recommended citation: Cristian F. Jara, Alejandro Ehrenfeld, Álvaro F. Egaña, Christian Vidal, Felipe A. Santibáñez-Leal. (2020). "Multi Pixel Stochastic Approach to Mineral Samples Spectral Analysis for Geometallurgical Modeling." Procemin Geomet. pp 1 - 17.
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Channelized facies recovery based on weighted compressed sensing

Published in 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016

A new image reconstruction algorithm is proposed based on weighted compressed sensing (WCS) for the problem of channelized facies recovery from pixel-based measurements.

Recommended citation: H. Calderón, F. Santibañez, J. F. Silva, J. Ortiz and Á. Egaña. (2015). "Channelized facies recovery based on weighted compressed sensing." 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM). Rio de Janerio, pp. 1-5.
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SOFI of GABAB neurotransmitter receptors in hippocampal neurons elucidates intracellular receptor trafficking and assembly

Published in Proceddings SPIE, 2013

The assembly of the GABABRs in hippocampal neurons with dual-color, 3D super-resolution optical fluctuation imaging (SOFI) is studied. SOFI is a fluorescence imaging modality which yields superresolved spatial resolution, 3D-sectioning and high image contrast.

Recommended citation: Anja Huss, Omar Ramírez, Felipe Santibáñez, Andrés Couve, Steffen Härtel, and Jörg Enderlein. (2013). "SOFI of GABAB neurotransmitter receptors in hippocampal neurons elucidates intracellular receptor trafficking and assembly." Proc. SPIE 8590, Single Molecule Spectroscopy and Superresolution Imaging VI. 85900N.
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Thesis

An information-theoretic sampling strategy for the recovery of geological images:modeling, analysis, and implementation

Published in Doctoral dissertation, Universidad de Chile, 2019

In this work, the formulation and experimental analysis of the Optimal Sensor Placement (OSP) problem has been investigated in the context of categorical 2-D models with spatial dependence.

Recommended citation: Santibáñez Leal, Felipe Andrés. (2019). "An information-theoretic sampling strategy for the recovery of geological images:modeling, analysis, and implementation." Doctoral dissertation, Electrical Engineering, Universidad de Chile. pp 1 - 153.
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