Wei Wang

Research Fellow

“We feel and know that we are eternal”

Baruch Spinoza

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Coeun Ham

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Profile

Coeun Ham is a third-year Monash University Electrical Engineering student with an AI minor.

She is completing a Monash Industry Experience Engineering placement with the Opportunity Tech Lab from 27 July to 23 October 2026. The placement includes 115 hours of supervised project work.

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Project focus

Coeun contributes to the AI in Virtual Reality and VRelovate research direction.

Her first work package develops a human-validated AI workflow that turns approved co-design evidence into filming-ready VR scripts and related filming materials.

Co-design evidence AI draft Human check VR script
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Current contribution

Coeun is reviewing the work-package brief and preparing a structured, evidence-based workflow before approved source material is added.

  • Map the existing VRelovate filming-script template.
  • Design a controlled input structure for approved evidence.
  • Create and test an AI-assisted draft-generation process.
  • Validate a de-identified example against its source evidence.
  • Prepare reusable documentation and handover materials.
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Supervision and boundaries

Placement supervisor: Dr Wei Wang.

  • Zhiyao Wang provides technical and project-context support.
  • The first work package focuses on a safe, human-validated workflow rather than direct development of the VRelovate platform.
  • Only approved, de-identified source evidence can be used.
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Related project

AI in Virtual Reality for Inclusive Employment Training

Profile

Coeun Ham is a third-year Monash University Electrical Engineering student with an AI minor. She is completing a Monash Industry Experience Engineering placement with the Opportunity Tech Lab from 27 July to 23 October 2026. The placement includes 115 hours of supervised project work.

Project focus

Coeun contributes to the AI in Virtual Reality for Inclusive Employment Training and VRelovate research direction. Her first work package develops a human-validated AI workflow that can turn approved co-design evidence into filming-ready VR scripts and related filming materials.

This work explores how AI can support content preparation while preserving evidence, accessibility requirements, responsible human oversight, and the practical structure needed for VR filming.

Current contribution

Coeun’s current work package includes:

  • mapping the existing VRelovate filming-script template and reference scripts;
  • designing a controlled input structure for approved evidence;
  • creating an AI-assisted draft-generation workflow;
  • producing and validating one de-identified micro-scenario against its source evidence; and
  • preparing reusable documentation and handover materials.

The initial work focuses on a bounded AI workflow rather than direct development of the VRelovate platform.

Supervision

  • Placement supervisor: Dr Wei Wang
  • Technical and project support: Zhiyao Wang
  • Placement context: Monash Industry Experience Engineering program

The placement uses scoped project access. Substantive work involving source material begins only with approved, de-identified evidence and agreed validation criteria.

Related project