Eun-Jung Holden


  • The University of Western Australia (M006), 35 Stirling Highway,

    6009 Perth


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Personal profile


Professor Eun-Jung Holden is the Director of UWA Institute of Data, and the leader of Centre for Data-driven Geoscience (CDG) at the School of Earth Sciences at UWA. She has leading expertise in data science applied to geoscience. Her research develops advanced machine learning, image analysis and visualisation methods to automate or semi-automate the interpretation of geoscientific data (geodata). Professor Holden’s multi-disciplinary research spans the boundaries of computational science and geoscience, and links academia with industry.

Professor Holden came to UWA as an international student from South Korea in 1985. She was trained and worked as a computer scientist at UWA. Her postgraduate and postdoctoral research focused on developing computer vision and visualisation algorithms for human motion recognition.

In 2006, she made a transition to geoscience at UWA. She established and currently leads the Geodata Algorithms Team that fosters a unique level of multi-disciplinary training and end-user focused research.

Through their innovative, transformational and interpretive data science solutions for geoscience end users, the team’s research achieved global research impact. Three suites of geodata analytics algorithms were commercialised in partnership with the world’s leading software vendors, namely CET Grid Analysis and CET Porphyry Detection extensions for Geosoft’s Oasis Montaj, in partnership with Geosoft (based in Canada); and Image Structure and Interpretation module for Advanced Logic Technology (ALT)’s WellCAD, in partnership with ALT (based in Luxembourg).  These products have been sold globally across the minerals and oil & gas industries.

Professor Holden has been leading major data science projects with Rio Tinto Iron Ore (RTIO) in recent years, UWA-RTIO Data Fusion Projects and the ongoing UWA-RTIO Blasthole Objective Logging Project.  This long-standing industry engagement resulted in the development of deployable machine learning methods and tools to analyse stratigraphy and their material compositions using diverse types of drill hole data, which resulted in three patent applications.  The CDG team at UWA uses machine learning, computer vision, spatial modelling and optimisation techniques to integrate diverse drill hole data including spectral, image, geochemistry and geophysics data to model material compositions, geomechanical proxies and their spatial distribution.  The team also develops advanced and interactive visualisation methods and tools to assist the mine pit mapping of geology in virtual reality.

In October, 2021, she became the inaugural Director of UWA Data Institute by bringing together 13 research clusters that applies data science across UWA to build a gateway to data intensive industries.  She is an ambassador for 'achieving industry outcomes from academic research' and fosters cross-disciplinary/industry collaboration.

Prof Holden won various awards, namely the Artificial Intelligence in Mining category of Women in AI Awards, Australia and New Zealand 2022; Women in Technology WA (WiTWA) Tech [20+] Awards, 2019; The UWA Vice Chancellor’s Award in Impact and Innovation, 2015; Laric Hawkins Memorial Innovation Award - the 23rd International Geophysics Conference and Exhibition, 2013; and Commendation in the Innovation Category of the WA Information Technology & Telecommunications Award, 2004.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 15 - Life on Land

Research expertise keywords

  • Resource data analytics
  • Automated pattern recognition
  • Mineral exploration data analysis
  • Geoscientific data mining
  • geodata analytics


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Collaborations and top research areas from the last five years

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