Dr Stephanie Baker ~ Lecturer, Electronic Systems and Internet of Things Engineering

Dr Steph Baker is a computer systems engineer with multidisciplinary research interests. Her main research interest is the use of artificial intelligence to solve significant problems in areas from healthcare to environmental science. Much of her research to date has focused on healthcare, which has allowed her to make significant contributions in health monitoring and prognostics assessment.

Steph holds a PhD in biomedical and software engineering and a Bachelor of Engineering (Computer Systems). She has taught at James Cook University since 2016, and joined the Cairns team as a full-time lecturer in early 2021.

Healthcare Research

Steph has undertaken substantial research in the intersection of healthcare and engineering. One of her key interests lies in enabling a higher standard of at-home and rural healthcare, which is vitally important in Northern Australia. Much of her research has focused on accurate measurement of health parameters using non-invasive and wearable technology. She is also interested in using machine learning for diagnosing illness and identifying likely outcomes to enable treatment decisions that are tailored to individual patients.

Other Research

Outside of healthcare, Steph is also interested in the environmental sciences. She is currently researching machine learning methods for improving the image quality of remote sensing data. This research will lead to tools that will support environmental and climate science applications.

Teaching

Steph has taught a variety of engineering subjects for various year levels, including EG1002 Computers and Sensors, EG1012 Electric Circuits, EE2201 Electric Theory, EE2300 Electronics 1, EE3600 Automatic Control 1, and EE4010 Analog Signals and Filters. Her teaching focuses on developing collaborative and engaging learning experiences that develop student's skills and confidence in the engineering context. Steph is also actively involved in supervising PhD candidates and undergraduate Honours projects.

Supervising

Steph is currently available to supervise PhD projects. If you are interested in a PhD in an area related to her research, then please contact her on stephanie.baker@jcu.edu.au with a CV, your research interests, and your previous research experience. Scholarships are available for PhD studies, but are highly competitive. Available projects are listed below, however Steph is happy to work with you to develop a new project in your area of interest.

Available Projects

The following project/s are currently available:

Machine learning for non-invasive vital sign measurement in premature babies 

In this project, the successful candidate will work to develop methods for non-invasively measuring vital signs and other health parameters in the neonatal intensive care unit setting, using data collected from the Townsville University Hospital. This project would suit a candidate who is passionate about healthcare with a background in computer engineering, data science, or a related field. This project is running in collaboration with Dr Yoga Kandasamy (Senior Neonatologist, Townsville University Hospital).

Teaching

• EE2300: Electronics 1 (Level 2; CNS)
• EE4010: Analog Signals and Filters (Level 4; CNS & TSV)
• EG1002: Computing and Sensors (Level 1; CNS)
• EG1012: Electric Circuits (Level 1; CNS)

Interests

Research

• machine learning
• healthcare
• rural and remote healthcare
• wearable sensors
• non-invasive health monitoring
• environmental sensing
• remote sensing

Experience

• 2021 to present - Lecturer, James Cook University (Cairns)

Research Disciplines

• Health services and systems (4203)
• Biomedical engineering (4003)
• Artificial intelligence (4602)

Socio-Economic Objectives

• Public health (2004)
• Information systems, technologies and services (2204)
• Specific population health (2005)

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles

• Baker S, Xiang W and Atkinson I (in press) A computationally efficient CNN-LSTM neural network for estimation of blood pressure from features of electrocardiogram and photoplethysmogram waveforms. Knowledge Based Systems,
• Baker S and Kandasamy Y (in press) Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review. Pediatric Research,
• Baker S, Xiang W and Atkinson I (2021) A hybrid neural network for continuous and non-invasive estimation of blood pressure from raw electrocardiogram and photoplethysmogram waveforms. Computer Methods and Programs in Biomedicine, 207.
• Baker S, Xiang W and Atkinson I (2021) Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates. Computers in Biology and Medicine, 134.
• Baker S, Xiang W and Atkinson I (2021) Determining respiratory rate from photoplethysmogram and electrocardiogram signals using respiratory quality indices and neural networks. PLoS ONE, 16 (4).
• Baker S, Xiang W and Atkinson I (2020) Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach. Scientific Reports, 10.
• Baker S, Xiang W and Atkinson I (2017) Internet of Things for smart healthcare: technologies, challenges, and opportunities. IEEE Access, 5. pp. 26521-26544

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Current

• Explainable AI for Medical Applications (PhD , Secondary Advisor)