Research Supervisor Connect

Data Processing for Sleep Monitoring

Summary

Research Area:

Signal processing, AI and deep learning, sleep staging and sleep disease analysis.

Supervisor

Associate Professor Omid Kavehei.

Research location

Biomedical Engineering

Synopsis

This project focuses on development of signal processing and AI methods and algorithms for sleep staging and sleep disorder analysis. The scope will include proposing dedicated AI and data science methods to explore and analyse relevant biomarkers and features with high sensitivity and specificity from physiological and behavioural signals; building data analytical models to enhance the learning performance, proposing approaches to improve model generalization; investigating explainable AI methods; developing information and computing schemes and algorithms for precise sleep disease detection and prediction.

Additional information

Successful candidates must have:

  • Bachelor’s or Master’s degree majoring in computer and data science, electrical and electronic engineering, biomedical engineering, microelectronics, telecommunication engineering, and related disciplines,
  • Good at signal processing and AI technologies,
  • Good communication skills,
  • Good at teamwork and collaboration.

How to Apply:

To apply, please email omid.kavehei@sydney.edu.au AND wei.chenbme@sydney.edu.au with the subject line “PhD Application”, and attach the following:

  • CV
  • Transcripts

Want to find out more?

Opportunity ID

The opportunity ID for this research opportunity is 3493

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