Ruebena Dawes is from Sydney, Australia, and is due to complete a Bachelor of Science (Advanced Mathematics) at The University of Sydney in 2017, with majors in applied mathematics and biochemistry. She began her degree with a broad interest in mathematics, and although she retains a deep appreciation and wonder for pure mathematics, she has decided her passion is in applying mathematics and mathematical principles to issues in the medical sciences. In addition, in the past year she has been learning a lot about computer science and big data and is excited to begin a career at the intersection of these three disciplines.
Mathematics in Medicine: Using Optimisation to Improve Cancer Treatment
Effective radiotherapy is dependent on being able to (i) visualise the tumour clearly, and (ii) deliver the correct dose to the cancerous tissue, whilst sparing the healthy tissue as much as possible. In the presence of motion, both of these tasks become increasingly difficult to perform accurately – increasing the likelihood of incorrect dose delivered to cancerous tissue and exposure of healthy tissue to unnecessary radiation, causing adverse effects. This project will develop mathematical optimisation tools to improve the quality of diagnostic images and treatment accuracy, and requires some programming experience.