The Statistics Research Group within the Research School of Finance, Actuarial Studies and Statistics (RSFAS) comprises staff with a broad range of expertise and research interests. Research conducted by members of the group has produced a strong and extensive publication record. The group’s research spans the following areas:
Statistical Theory and Methods including nonparametric and semiparametric methods, functional data analysis, models for spatio-temporal and correlated data, survey analysis, time series analysis, network data modelling and non-Euclidean statistics.
Probability and Stochastic Processes including Lévy processes, stochastic calculus, martingales and Markov processes, diffusion and jump processes, stochastic differential equations, limit theorems, high-dimensional probability and Poisson-Dirichlet distributions.
Data Science including statistical machine learning, high-dimensional statistics, computational methods, data visualisation, statistical software development (particularly R packages), and Bayesian methods.
Applications of probability and statistics in various disciplines, including actuarial science and insurance risk, mathematical finance, agriculture and biometry, biostatistics and bioinformatics, Earth sciences and geophysics, ecological and environmental studies, forensic sciences, social sciences, and other fields.
Much of our research is multidisciplinary, with staff collaborating across the University and with government agencies such as the Mathematical Sciences Institute, School of Computing, Crawford School of Public Policy, National Centre for Epidemiology and Population Health, Research School of Biology, Research School of Earth Sciences, the Statistical Support Network, Department of Agriculture, Fisheries and Forestry, CSIRO, Geoscience Australia, and the Australian Bureau of Statistics.
A distinguishing feature of our research group is the high level of international collaboration among its members, fostered by a vibrant seminar and visitor program and an annual research workshop.
Further information about research interests can be found on the profile pages of the Statistics faculty.
NEWS
Grant success
Congratulations to Janice Scealy, who has been awarded an ARC Future Fellowship to develop new geometry-driven statistics tools tuned to reveal vital geological clues. The award is valued at $1,329,806.00.
Top publication
Congratulations to Kassel Hingee, Janice Scealy and Andy Wood for their Journal of American Statistical Association publication!
Editor appointment
Emi Tanaka is now the Chief Editor of the R Journal
Award
Janice Scealy was awarded the 2025 ANU College of Business and Economics Research Award for Excellence in Research Engagement & Social Impact.
ARC Discovery Grant
Congratulations to Francis Hui and Yanrong Yang for their separate ARC Discovery Grant 2025 successes!
Top publications
Congratulations to Francis Hui for his publication in the Journal of the American Statistical Association; and to Jiazhen Xu, Andy Wood and Tao Zou for their publication in Biometrika. Both journals are top Statistics journals.
Recent selected publications
QTLs for heat-induced stomatal anatomy underpin gas exchange variation in field-grown wheat
Chaplin, E., Tanaka, E., Merchant, A., Sznajder, B., Trethowan, R., & Salter, W. (2026), Frontiers in Plant Science
Principal subsimplex analysis
Lee, H., Hingee, K.L., Scealy, J.L., Wood, A.T.A., Grunsky, E. & Marron, J.S. (2026) Forthcoming in the Journal of Computational and Graphical Statistics
Professors Joe Gani and Chris Heyde and Their Contributions to Finance and Risk Management
S Liu, S., Maller, R., & Rachev, S. T. (2026). Journal of Risk and Financial Management
Limit theorems for the Pitman-Yor frequency spectrum
Maller, R., & Shemehsavar, S., (2026). Mathematics, Biology
Probabilistic risk assessment of bird-turbine collisions using flight path models
Shemehsavar, S., Hocking, G., Maller, R., Fleming, P.A., Mansoor, W. (2026). Proc. of the European Safety and Reliability Conference (ESREL2026)
Quantifying the missingness of Indigenous status from two administrative sources in regional Australia using capture-recapture methods
Thandrayen, J., Maestrini, L., Riley, T., Lovett, R., Draper, G., Dillon, Y., Freebairn, L. (2026). Population Research and Policy Review
Nonparametric Bootstrap Inference for the Eigenvalues of Geophysical Tensors
Hingee, K, Scealy, J. & Wood, A. (2026). Forthcoming in the Journal of the American Statistical Association
