Stephanie Baker

Dr Steph Baker is a computer systems engineer with multidisciplinary research interests. Her core research interest is the development and use of responsible artificial intelligence systems 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 have significant impact in health monitoring and prognostics assessment.

Steph holds a PhD in biomedical and software engineering. Her doctoral thesis was awarded the Dean's Award for Research Higher Degree Excellence. Steph also holds a Bachelor of Engineering (Computer Systems) with Class I Honours. She has taught at James Cook University since 2016, joining the Cairns team in early 2021.

Responsible Artificial Intelligence

Steph specialises in responsible AI, which involves making AI systems transparent, fair, and accountable to human users. She is particularly interested in how AI decisions can be explained to non-technical end-users in a way that is interpretable and acceptable, as well as improving the fairness of AI systems through these explanations. Responsible AI has applications in many domains, including healthcare, autonomous vehicles, and generative AI systems such as ChatGPT. Steph has established the JCU Responsible Artificial Intelligence research group at JCU Cairns. 

If you are interested in joining the JCU Responsible Artificial Intelligence research group, email Steph (stephanie.baker@jcu.edu.au) with your CV, previous academic transcripts, and (optionally) your research project proposal.

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 responsible artificial intelligence for diagnosing illness and identifying likely outcomes to enable treatment decisions that are tailored to individual patients. Steph has leveraged her AI expertise to collaborate with multidisciplinary healthcare research groups including the Townsville University Hospital and CSIRO's Australian eHealth Research Centre.

Other Research

Steph is also interested in applying responsible artificial intelligence to other domains for positive social and environmental impact. Recently, Steph lead the application of AI methods for filling data gaps in cloud-affected remote sensing data in collaboration with Geoscience Australia.

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, EE4010 Analog Signals and Filters, and EG4011+EG4012 Thesis. Her teaching philosophy focuses on flexible, collaborative and engaging learning experiences that develop student's skills and confidence in the engineering context. She has also developed innovative assessments that responsible use of AI tools, building future-ready graduates. Steph is actively involved in supervising PhD candidates, Masters research projects, 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:

Artificial intelligence for non-invasive vital sign measurement in premature babies

In this project, the successful candidate will work to develop responsible artificial intelligence 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).

Current Funding

The following projects are currently funded:

Northern Australia Regional Digital Health Collaborative (NARDHC)

Project title: Fusion of wearable and environmental sensors for remote monitoring of health and wellbeing in elderly populations.

Indicative funding: $48,063 over six months

Summary: This project aims to develop a smart home health monitoring prototype that improves upon existing technology by fusing information from multiple sensors. The proposed system will use non-invasive wearable sensors, non-contact mmWave technology, and artificial intelligence to monitor key vital signs, physical activity, stress, fatigue, and environmental conditions. The goal of this project is to prototype a comprehensive system for monitoring health and wellbeing in rural and remote Australia, with particular focus on elderly persons.

Investigators: Stephanie Baker, Euijoon Ahn, Tao (Kevin) Huang, Bronson Philippa, Caryn West, and Christopher Rouen.

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Townsville Hospital and Health Service (THHS) Study, Education, and Research Trust Account (SERTA) Fund

Project title: Machine Learning Method for Measuring Blood Pressure and Monitoring Renal Perfusion Non-Invasively in the Neonatal Intensive Care Unit

Indicative funding: $29,999 

Summary: This project aims to develop responsible artificial intelligence algorithms capable of continuously monitoring blood pressure and acute kidney injury risk in babies born very preterm. It is expected that this work will provide non-invasive alternatives  for measuring these key parameters, in turn leading to improved patient outcomes. This work also has significant potential to support critical care in low-resource and remote areas.

Investigators: Stephanie Baker, Yoga Kandasamy

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Northern Australia Regional Digital Health Collaborative (NARDHC)

Project title: A mobile app and dashboard for effective management of early-stage chronic kidney disease

Indicative funding: $48,724 over six months

Summary: The incidence and prevalence of chronic kidney disease (CKD) varies globally, and people in the lowest socioeconomic quartile have a 60% higher risk of progressive CKD. This project aims to develop a mobile app that detects vulnerable individuals who are at risk of deterioration in renal function and are needing intervention, while also allowing monitoring and appropriate education to those who are progressing steadily. The expected outcome is a novel mobile analytic app that can improve the management of CKD patients in rural and remote areas for better health outcomes and planning.

Investigators: Euijoon Ahn, Jason Holdsworth, Stephanie Baker, Konrad Kangru, Krishan Madhan

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