Jim Moraga

Jim Moraga
Colorado School of Mines · Department of Mining Engineering

PhD

About

8
Publications
772
Reads
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6
Citations
Introduction
Developing and implementing novel approaches to remote sensing and machine learning applied to Earth Resources Development, with a focus on Deep Learning, Multispectral and Hyperspectral data
Additional affiliations
April 2014 - October 2017
PricewaterhouseCoopers
Position
  • Consultant
Description
  • Consulting Mining Leader for the US - Lead client relationship for key accounts in the region - Support teams on Mining clients - Bring expertise from PwC's network of 1,500+ mining professionals to our Global and Local accounts - Ensure quality of delivery for our consulting services in mining Mining Leader for Latin america - Lead client relationship for key accounts in the region - Support local teams on Mining - Bring expertise from PwC's network of 1,500+ mining professionals to our Global
June 2008 - February 2014
Partners in Performance
Position
  • Associate Principal
Description
  • Ensure proper execution and achievement of targets in engagements, build the firm's reputation and intellectual property, manage and grow the relationship with the client Area Engagement Manager - Identified and valued improvements in capital project for an Iron miner in Chile that increased NPV by 60%+ - Trained and coached the Strategic Sourcing group of major Copper miner in South America - Led strategic sourcing initiative in HME, parts and maintenance for Mining company
September 2004 - March 2007
McKinsey
Position
  • Consultant
Description
  • - Estimated operational improvement potential of acquisition target in the insurance industry for leading equity firm in Brazil - Designed triple play (TV, broadband, phone) go-to-market strategy and tactics for leading telecom provider in Chile - Evaluated and designed bottom of the pyramid strategy and go-to-market tactics for leading mobile operator in Africa, potential increase of 100% in EBITDA - Diagnosed and corrected IT organization and its development process for leading energy retailer
Education
January 2019 - May 2021
Colorado School of Mines
Field of study
  • Earth Resources and Development
September 2001 - April 2005
University of Michigan
Field of study
  • Business Administration
March 1990 - September 1994
University of Santiago, Chile
Field of study
  • Computer Engineering (Licenciatura en Ciencias de la Ingeniería)

Publications

Publications (8)
Conference Paper
Monitoring dam failures using satellite images provide first responders with efficient management of early interventions. It is also equally important to monitor spatial and temporal changes in the inundation area to track the post-disaster recovery. On January 25th, 2019, the tailings dam of the Córrego do Feijão iron ore mine, located in Brumadin...
Preprint
Full-text available
Monitoring dam failures using satellite images provide first responders with efficient management of early interventions. It is also equally important to monitor spatial and temporal changes in the inundation area to track the post-disaster recovery. On January 25th, 2019, the tailings dam of the Córrego do Feijão iron ore mine, located in Brumadin...
Presentation
Full-text available
Underground environments pose unique challenges to machine-generated maps and object recognition, including: inadequate light sources, constrained locations, irregular surfaces, unavailability of GPS, unique semantics, and no standard databases for training and testing. Our research consists in: a) applying a variety of sensors (e.g.: LiDAR, RGB-D...
Presentation
Full-text available
In this study, we present an approach for monitoring the inundation area due to a tailings dam failure using satellite images and machine learning. We used Sentinel-2 images to map the inundation area around Brumadinho tailings dam (January 25th, 2019), and delineate land use and cover impacted by the dam failure. We classified satellite images of...
Article
Full-text available
The availability of free and high temporal resolution satellite data and advanced SAR techniques allows us to analyze ground displacement cost-effectively. Our aim was to properly define subsidence and uplift areas to delineate a geothermal field and perform time-series analysis to identify temporal trends. A Persistent Scatterer Interferometry (PS...
Preprint
Full-text available
This article describes the performance of JigsawHSI,a convolutional neural network (CNN) based on Inception but tailored for geoscientific analyses, on classification with the Indian Pines, Pavia University and Salinas hyperspectral image data sets. The network is compared against HybridSN, a spectral-spatial 3D-CNN followed by 2D-CNN that achieves...
Article
Exploration of geothermal resources involves analysis and management of a large number of uncertainties, which makes investment and operations decisions challenging. Remote Sensing (RS), Machine Learning (ML) and Artificial Intelligence (AI) have potential in managing the challenges of geothermal exploration. In this paper, we present a methodology...
Preprint
Full-text available
Monitoring dam failures using satellite images provides first responders with efficient management of early interventions. It is also equally important to monitor spatial and temporal changes in the inundation area to track the post-disaster recovery. On January 25th, 2019, the tailings dam of the C\'orrego do Feij\~ao iron ore mine, located in Bru...

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Projects

Project (1)
Project
Applying new machine learning techniques to analyze remote-sensing images, with the goal of developing a process to identify the presence of blind geothermal resources based on surface characteristics. Colorado School of Mines will develop a methodology to automatically label data from hyperspectral images of Brady’s Hot Springs, Desert Rock, and the Salton Sea.