Wearable sensing for health monitoring
Research Areas
I am looking for highly motivated PhD students to work on wearable sensing and computing for health monitoring.
Requirements
- Strong background in computer science, electrical engineering, or related fields
- GPA of at least 82 for University of Melbourne students and at least 85 for external universities
- Experience in data collection, hardware, sensing, and computing
- Solid programming skills, including Python and C++
- Relevant publications in top-tier venues such as UbiComp, HotMobile, etc
Contact
- If you are interested, please email ting.dang@unimelb.edu.au with your CV, transcripts, and research proposal. Please review my recent publications to identify overlapping research interests when preparing your proposal. I will respond to applications that include all required documents. Due to the high volume of inquiries, I may not respond to all emails.
Continuous glucose monitoring (CGM) has revolutionized the management of type 1 diabetes. The continuous acquisition of glucose readings, combined with other physiological and biochemical data from electronic medical records, provides extensive and detailed insights into the daily fluctuations of glucose levels and associated physiological changes. Artificial intelligence (AI) has been increasingly employed to analyze these health data sets, facilitating personalized care for individuals with diabetes and enabling the adaptation of treatments for complex clinical presentations.
This PhD project aims to investigate the application of AI in analyzing glucose signals to identify individuals at high risk and diagnose those who may develop severe hypoglycemia or other diabetes-related complications. Specifically, the objectives of this project are:
- To develop AI algorithms for CGM data to identify high-risk individuals and improve diabetes management
- To integrate multimodal data for enhanced diabetes monitoring
- To develop personalized models for the management of diabetes
Supervisors: Prof. Elif Ekinci and Dr. Ting Dang, University of Melbourne
Anticipated start date: Early 2025
Requirements
- Master degree in computer science or related fields
- Weighted Average Mark (WAM) > 85/100 (82 for Unimelb Students)
- Relevant publications in top venues
How to Apply
To apply for this position, please send the following documents to Ting Dang (ting.dang@unimelb.edu.au):
- CV
- Academic transcripts
- A brief statement of research interests (1-2 pages)
- Samples of published papers