Background
Background
I am currently a Research Technician at CSIRO’s Data61. I obtained my Ph.D. from the Australian National University in his thesis titled: Medical Consumer Question Answering: Challenges and Approaches under the CSIRO Data61 PhD Scholarship Program and the Australian Research Training Program. I am currently working on providing climate adaptation management advice to farmers using Large Language Models (LLMs) as part of the Climate Services for Agriculture (CSA) project.
I have published papers in many major international conferences such as the Association for Computing Machinery’s Special Interest Group on Information Retrieval (SIGIR), the Conference on Information and Knowledge Management (CIKM) and Association for Computational Linguistics (ACL). For my undergraduate degree I an honour’s degree in Science (adv.) majoring in nanoscience and technology, and computer science.
My topic for my thesis is Consumer Medical Question Answering: Challenges and Approaches. I am researching into developing strategies for translating success found in open-domain Question Answering research, adapting and applying them to the biomedical and software engineering domains. In particular, for the biomedical side of things, I aim to research methods into improving patient QA to allow patients who self-diagnose to get valuable feedback in how likely their disease is to be, the risks and if this requires medical attention. Studies have shown that almost a third of patients who search their symptoms online and self-diagnose do not seek a second medical opinion afterwards leading to a potential detriment in health (a patient who believes they are terminally ill might take actions they otherwise might not have). Furthermore, patients who do look up their symptoms online have shown to have better rapport with their medical examiners due to a greater awareness of their symptoms and diseases.