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Research
PhD Candidate at RMIT University · Collaborative AI · Multi-Agent Systems & Human-AI Interaction
Research Focus
Investigating frameworks for AI-AI interaction (multi-agent systems) and AI-Human interaction to solve complex problems in sustainable environments. Primary application domain: Education Technology (EdTech). The work sits at the intersection of agent orchestration, conflict resolution between autonomous agents, and the human factors that drive trust and effective collaboration with AI.
Institution
RMIT University
Field
Collaborative AI
Method
Mixed Methods
Research Questions
- ▹RQ1 — How can AI agents collaborate effectively in multi-agent systems?
- ▹RQ2 — What factors influence human trust and acceptance when interacting with AI?
- ▹RQ3 — What design is optimal for collaborative AI systems in educational environments?
Methodology
A mixed-methods design combining controlled lab experiments with qualitative interviews. Preliminary results indicate that AI interface design significantly impacts user trust and collaboration effectiveness.
Quantitative
- Controlled lab experiments
- Eye tracking & EEG
- Structured surveys
Qualitative
- Semi-structured interviews
- Thematic analysis