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Email

eunjung.holden@unimelb.edu.au

Credentials


Position
Professor of Digital Innovation
School of Computing and Information Systems
ORCID

0000-0002-8752-1639

Prof Eun-Jung Holden

Professor of Digital Innovation
School of Computing and Information Systems

88 Scholarly works
1 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Deep-learning-based hybrid model with iterative lithology constraints for the enhanced prediction of missing well-logs
    DOI: 10.1016/j.cageo.2026.106106
  • 2026

    Conference Proceedings

    From Metrics to Meaning: A Three-Layer DCI Framework of Generative AI Adoption and Intellectual Governance
  • 2026

    Book Chapter

    Paired Hierarchical VAEs for Image-to-Image Translation and Cross Reconstruction
    DOI: 10.1007/978-981-95-4972-6_12
  • 2026

    Journal article

    Protecting Autonomy and Competence: Learner Identity and the Struggle between Cognitive Offloading and Effective Practice with GenAI
    DOI: 10.24135/pjtel.v8i1.245
  • 2025

    Journal article

    Implicit neural representation for potential field geophysics
    DOI: 10.1038/s41598-024-83979-z
  • 2025

    Research contracts (non-grants)

    ChatGeo: Forging Trust in Spatial Semantic Document and Knowledge Retrieval
  • 2025

    Journal article

    Haromonic Curvature and Bedding Uncertainty Across Scales
    DOI: 10.5194/egusphere-egu24-7785
Eun-Jung Holden

Latest Honours,
Awards and Fellowships


2022
Women in AI Awards Australia New Zealand (AI in Mining)
2019
Women in Technology, WA (WiTWA) Tech [20+] Awards
2015
The UWA Vice Chancellor’s Award in Impact and Innovation

RECENT SCHOLARLY WORKS

  • 2024

    Journal article

    Automated geological logging from FTIR reflectance spectra utilising geochemical and historical logging constraints
    DOI: 10.1016/j.oregeorev.2024.106004
  • 2023

    Conference Proceedings

    Workshop on Document Intelligence Understanding
    DOI: 10.1145/3583780.3615312
  • 2023

    Journal article

    Anomaly detection in Fourier transform infrared spectroscopy of geological specimens using variational autoencoders
    DOI: 10.1016/j.oregeorev.2023.105478
  • 2022

    Journal article

    Magnetic grid resolution enhancement using machine learning: A case study from the Eastern Goldfields Superterrane
    DOI: 10.1016/j.oregeorev.2022.105119

Acknowledgement of Country

We acknowledge Aboriginal and Torres Strait Islander people as the Traditional Owners of the unceded lands on which we work, learn and live. We pay respect to Elders past, present and future, and acknowledge the importance of Indigenous knowledge in the Academy.

Read about our Indigenous priorities

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Phone: 13 MELB ( 13 6352)

International: +61 3 9035 5511


Address:
The University of Melbourne
Grattan Street, Parkville,
Victoria, 3010, Australia

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