Sally Cripps
Honorary Professor Faculty of Engineering and Information Technology at University of Sydney/Honorary Professor of Statistics at Macquarie University
Links
Biography
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Sally Cripps is currently the Research Director of Analytics & Decision Sciences at Data61 within CSIRO. She is an internationally recognised scholar and Professor in Bayesian statistics, a Professor of Statistics at the University of Sydney and previously the Director of the ARC Centre in Data Analytics for Resources and Environments (DARE Centre). She holds a bachelor degree in Chemical Engineering from the University of Sydney, an MBA from the University of Western Australia and a PhD in statistics from the University of NSW. She is also Chair of the International Society for Bayesian Analysis’s section Bayesian Education and Research in Practice.
Sally’s research focus is the development of new and novel probabilistic models which are motivated by the need to solve an applied problem with the potential for impact. She has particular expertise in the use of mixture models for complex phenomenon, modelling longitudinal data, nonparametric regression, the spectral analysis of time series, and the construction of transitions kernels in MCMC schemes which efficiently explore posterior distributions of interest.
Sally has extensive experience in translating world leading novel data science models to deliver practical, evidence driven solutions for industry and government. Sally has advised some of Australia’s leading organisations including CBA, McKinsey, Newcrest, The Nature Conservancy, NSW Government, Ramsay Health and is developing collaborative projects with the DARE Centre industry partners.
Research interests
- Bayesian modelling of longitudinal and panel data
- Spectral Analysis
- Mixture Models for time series
Videos
Models & Uncertainty in the time of COVID19 - Sally Cripps - WA Statistical Society of Australia
COVID-19 data modelling 'consistently inaccurate'
Raising the Bar for Australian Data Science
Precipitation reconstruction from climate-sensitive lithologies using Bayesian machine learning
The Alan Turing Institute: Data Centric engineering and the Built Environment | CogX 2020
Did the models fail? - Sally Cripps
Models And Uncertainty In The Time Of COVID-19 - Sally Cripps
A Tale of 》2 Models - Prof Sally Cripps at the METRICS International Forum
Where Angels Fear to Tread... the use and misuse of Graphical Models
Data Uncertain conference 2020 Q&A - Health
Predicting poor functional trajectories to facilitate early intervention in youth mental health
The 2020 Statistical Science Lecture
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