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A Neural Fuzzy Fusion Engine for Human-Machine Autonomous Systems

  • Full or part time
  • Application Deadline
    Applications accepted all year round
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Abstract: This project aims to develop an intelligent engine to adaptively fuse multiple trust-based information from various agents in human machine autonomous systems (HMAS). The significance of this research is to develop new techniques to detect covert-state drift, model trustworthiness between humans and machines, and adaptively fuse information under various kinds of uncertainty and trust levels. These techniques will be integrated to produce a general framework to facilitate human-machine interaction and enable better collaborative decisions in HMAS. The outcomes will benefit human-centric automation systems in general and next-generation autonomous vehicles in particular, which will contribute to the Australian economy.

Funding Notes

1. Strong backgrounds in Artificial Intelligence (AI), Brain-Computer Interface (BCI), Virtual Reality (VR), Augmented Reality (AR), Computational Intelligence or Cognitive Neuroscience.
2. GPA falls into the top 30%, or alternatively average score of subjects recorded in official transcript(s) no less than 85.0. (or alternative equivalence due to grading system)
3. Majoring in Science or Engineering, like Math, Physics, Information Science, Computer Science, Biomedical Science, Electrical Engineering (Signal Processing), etc.
4. Very strong programming knowledge about Matlab, Python, Java, C++, Unity, etc.
5. Enthusiasm for research

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