Scott is Professor and Head of Statistics in the School of Mathematics and Statistics at UNSW. He is internationally recognised for his work in computational and Bayesian statistics, and in particular for developing inferential techniques for computationally intractable models and challenging data. Scott is currently President of the Statistical Society of Australia, Chair of the Australiasian Chapter of the International Society of Bayesian Analysis (ISBA) and a member of the Australian National Committee for Mathematical Sciences. Scott is a previous winner of the Moran Medal (Australian Academy of Science), the G. N. Alexander Medal (Engineers Australia) and the J. G. Russell Award (Australian Academy of Science), and is a previous Australian Research Council Queen Elizabeth II Research Fellow.
Computationally intractable models
Extreme vaule theory
Monte Carlo Methods
Symbolic data analysis
Ph.D. in Statistics, Bristol University, U.K.
M.Sc. in Environmental Statistics and Systems, Lancaster University, U.K.
B.Sc. in Mathematics and Statistics, Lancaster University, U.K.
This research deals with the field of symbolic data analysis. Researchers have developed ways of estimating how components of the underlying data mix and interact to produce the values of the symbols they observe. So the models they build relate more closely to what's really happening.
A fundamental challenge in constructing Big Models is the question of calibration. Big Models typically have a large number of parameters, which need to be inferred from data in a robust and theoretically justifiable way. Approximate Bayesian Computation is one promising approach to tackle this calibration problem for large complex models.
Prizes, awards and special recognition
2017 Future Fellowship was awarded to Scott Sisson. Awarded from the Australian Research Council.
G. N. Alexander Medal for Hydrology and Water Resources was awarded to Scott Sisson. Awarded from the Engineers Australia.