Rate My Professor Thomas Fung

Macquarie University

4.5

4 reviews · out of 5

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Ratings & reviews

5.08/20/2025

Makes even hard topics easy to grasp.

4.05/21/2025

Fair, constructive, and always motivating.

4.02/27/2025

A true role model for academic success.

5.02/17/2025

Helps students see the bigger picture.

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About Thomas

Thomas Fung is an Associate Professor in the School of Mathematical and Physical Sciences at Macquarie University, within the Faculty of Science and Engineering. He earned his PhD in Statistics from the University of Sydney in 2010 and a B.Sc. in Advanced Mathematics with First Class Honours from the same university in 2006. In his current roles as Director of Education and Deputy Course Director for the BSc program, Fung has significantly contributed to statistical education and curriculum development. His career at Macquarie University includes leadership in teaching initiatives, such as convening units like STAT1378 Coding and Communication in Statistics, STAT3175 Linear Models, and STAT1379 Statistical Technologies for Data Science.

Fung's research centers on integer-valued time series analysis, flexible regression models, Conway-Maxwell Poisson and related distributions, extreme value theory, and financial modelling, with a focus on complex data featuring dispersion, zero-inflation, skewness, and heavy-tailedness. Notable publications include 'Tail dependence for two skew t distributions' (Fung and Seneta, 2010, Statistics & Probability Letters), 'Modelling and estimation for bivariate financial returns' (Fung and Seneta, 2010, International Statistical Review), 'The t-distribution in financial mathematics and multivariate testing contexts' (Seneta and Fung, 2025, Journal of Risk and Financial Management), 'A theorem on the asymptotics of skew-normal type integrals' (Fung and Seneta, 2024, Statistics and Probability Letters), and 'On exponential-family INGARCH models' (Huang et al., 2025, Journal of Time Series Analysis). He has produced 33 research outputs, including contributions to environmental science such as 'Inconsistent coral bleaching risk indicators between temperature data sources' (Neo et al., 2023, Earth and Space Science). Fung supervises postgraduate research and coursework students on topics like semiparametric generalised linear models and CMP time series models. His influence is evident in awards such as the Faculty of Science and Engineering Excellent Award for Educational Leader (2023), multiple Teaching Development Grants (2022-2024), and the Award for Inter-School Collaboration (2023). He serves as Associate Editor for the Australian and New Zealand Journal of Statistics and the R Journal, and holds leadership positions including former President of the Statistical Society of Australia NSW Branch, elected member of the International Statistical Institute, and Summer School Officer for the International Association of Statistical Computing. Fung has organized the Australian Statistical Conference 2023 and delivered lectures on statistics education, such as 'Statistics: Your Ticket to Anywhere' (2019, 2020, 2021).