Edward Cripps

Associate Professor, , BEc W.Aust., BSc PhD NSW

  • The University of Western Australia (M019), 35 Stirling Highway,

    6009 Perth

    Australia

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Personal profile

Research

I am a statistician with research interests in Bayesian longitudinal analysis, spatio-temporal models and the integration of physical and probabilistic models. My primary applications are environmental, meteorological and oceanographic processes and their influence on engineering decision making  and  resource management. Australian natural resource industries and environmental bodies are experiencing an unparalleled growth in the quantity of available data. Together with the increasing availability of computer based modelling and simulation, the so called Data Sciences and its mathematical underpinnings are firmly entrenched in scientific inference and industrial decision making. My research examines model/data missmatch and its impact on inference and decisions, using high quality, rather than high quantity, data to integrate our mathematical abstractions of the world with probabilistic approaches to uncertainty quantification.

Funding is available through joint government/industry grants for potential PhD candidates and post-doctoral researchers -- see funding overview below.  Those interested in the above approach to data science are encouraged to contact me about such opportunities.

Industrial relevance

The increasing need for (a) rigorous data science applications and (b) the development of statistical methodology to address more complex problems  has resulted in my collaboration and/or consultation with many industrial and governmental bodies.   Most recently, these have included INPEX, Shell Australia, Woodside Engergy, Bureau Veritas - France, Lloyd's Register Global Technology Centre, Fugro Australia Marine, Wood Group Kenny Australia, Geosciences Australia, Newcrest Mining, McKinsey & Company, IAG Insurance, ALCOA of Australia, BHP Billton, Roy Hill Holding, CORE Innovation Hub, NSW Natural Resources Commission, NSW Office of Environment and Heritage, Western Australia Biodiversity Science Institute, Bureau of Meteorology, Water NSW, Alan Turing Institute (UK).

Funding overview

* 2021--2025 ARC Industrial Transformation Research Hub for Transforming Energy Infrastructure Through Digital Engineering.  University of Western Australia.  Approx. $10 million. Personal Role: Chief Investigator and UWA Data Science Leader.

* 2020--2024 ARC Industrial Transformation Training Center for Data Analytics for Resources and Environment. University of Sydney.  Approx. $8 million. Personal Role: Deputy Director, Chief Investigator and UWA Node Leader.


* 2019--2023 ARC Inudstrial Transformation Training Centre  for Transforming Maintenance Through Data Science. Curtin University of Technology. Approx $8 million. Personal Role: Chief Investigator.

*2016--2020 ARC Industrial Transformation Research Hub for Offshore Floating Facilities.  University of Western Australia.  Approx $10 million. Personal Role: Chief Investigator and Data Science Leader.

 

Teaching overview

In 2022 I am teaching

  • STAT2063 Probabilistic Methods and Their Applications.  A first semester course (2nd year) in probability for engineers 
  • STAT1520 Economics and Business Statistics.  A Second Semester applied statistics unit (1st year) for economics and business students.

Current projects

Other projects I am currently involved with and which are available include

 

Duffin, C., Cripps, E., Stemler, T. and Girolami, M.  "Low rank statistical finite elements for scalable model-data synthesis".  Available at https://arxiv.org/abs/2109.04757

 

Scalzo, R., Lindsay, M., Jessell, M., Pirot, G., Giraud, J., Cripps, E. and Cripps, S.  "Blockworlds 0.1.0: A demonstration of anti-aliased geophysics for probabilistic inversions of implicit and kinematic geological models", submitted to Geoscientific Model Development.  Available at https://gmd.copernicus.org/preprints/gmd-2021-187/

 

Bertolacci, M., Cripps, E., Rosen, O. and Cripps, S.  "A comparison of methods for modeling marginal non-zero daily rainfall across the Australian Continent." Available at https://arxiv.org/abs/1804.08807

Industry keywords

  • Environmental
  • Mining and Resources
  • Government

Research expertise keywords

  • Computational statistics
  • Bayesian statistics
  • Applied statistics
  • Mixture modelling
  • Spatial/temporal modelling