Rate My Professor Colin Zhang

Zhang's research focuses on life cycle models, optimal control, financial strategies, derivative pricing, retirement villages, and residential aged care. Affiliated with the Transforming Energy Markets Research Centre, Emerging Risks Research Centre, and FinTech and Banking Research Centre, he has produced 22 research outputs, including key publications such as 'Optimal life insurance and annuity demand under hyperbolic discounting when bequests are luxury goods' (2021), 'Time trends in losses from major tornadoes in the United States' (2023), 'Predicting non-emergency healthcare use in Australia using machine learning on longitudinal household data' (2026), 'Expected length of stay in residential aged care facilities in Australia: Assessing the impact of dementia using machine learning' (2025), and 'Optimal decision-making for consumption, investment, housing, and life insurance purchase in a couple with dependent mortality' (2025). His awards include the Adobe Innovation Grant (2021), MQBS Research Impact Awards (2022), and Excel for Business grant (2017) for fostering learning communities. Zhang leads projects developing online calculators for aged care financing, evaluating factors like deposits, fees, means tests, and pensions in collaboration with colleagues including Associate Professor Timothy Kyng, Professor David Pitt, and Dr. Sachi Purcal. These tools, extending prior retirement village analyses, have attracted media coverage and links on consumer sites such as the Council on the Ageing and ASIC. He also advances teaching through AI-driven automation for assessment and feedback in Statistics and Finance units using Excel and VBA integrated with ChatGPT.