Scott Sisson

Professor Scott Sisson is Director of the UNSW Data Science Hub (uDASH) and Professor of Statistics and Data Science at the University of New South Wales, School of Mathematics and Statistics. His research focuses on computational statistics, particularly solving 'intractable' statistical problems through Bayesian methods, big data techniques, simulation algorithms, and extreme value theory with environmental applications.

Education includes a PhD in Statistics from Bristol University (2002), MSc in Environmental Statistics from Lancaster University (1997), and BSc in Mathematics and Statistics from Lancaster University (1996). Research interests span:

• Bayesian statistics and uncertainty quantification
• Big data analytics and scalable algorithms
• Machine learning integration with statistical methods
• Extreme value modeling for climate/environment
• Computational techniques for intractable problems

Recent publications (2022-2025) demonstrate strong emphasis on Bayesian computation, spatiotemporal modeling, and interdisciplinary applications in materials science, oncology, quantum computing, transportation policy, and ecology. Methodological innovations include likelihood-free inference, modular Bayesian analyses, and symbolic data modeling.

Awards and honors:

• 2020 Service Award (Statistical Society of Australia)
• 2017 ARC Future Fellowship
• 2015 G. N. Alexander Medal (Engineers Australia)
• 2011 Moran Medal (Australian Academy of Science)
• 2010 J.G. Russell Award (Australian Academy of Science)
• 2010 Queen Elizabeth II Research Fellowship

As Director of uDASH, he leads data science initiatives across UNSW. He maintains sustained ARC funding and supervises students in computational statistics, Bayesian methods, extreme value theory, and machine learning. Professional service includes editorial roles for Statistics and Computing and past presidency of Statistical Society of Australia.