Kelly’s research focuses on Bayesian statistics, machine learning, dimension reduction techniques in Big Data, and time-varying parameter models. Kelly has a strong interest in developing new model specifications, and applying statistics models and machine learning algorithms in applied research areas such as bioinformatics, health and economics. Prior joining in JCU, Kelly worked as a Data Scientist at Data61, CSIRO and received a PhD degree at the University of Queensland in 2018.



-  "Emergency departmnet waiting time prediction in real-time"  funded by the Emergency Medicine Foundation, $36,733 https://emergencyfoundation.org.au/projects/emergency-department-waiting-time-predictions-in-real-time/


  • MA3832: Neural Network and Deep Learning (Level 3; CNS & TSV)
  • MA5832: Data Mining and Machine Learning (Level 5; CNS & ONL)
  • MA5852: Data Science Master Class 2 (Level 5; ONL & TSV)
  • Bayesian statistics
  • Dimension reduction techniques in Big Data
  • Machine learning algorithms
  • Biostatistics
  • Time-varying parameters
  • Macroeconomics
  • 2017 to 2019 - Data Scientist, Data61,CSIRO (Brisbane)
  • 2013 to 2017 - UQ Scholarship for Post Graduate Students
  • 2013 to 2014 - Distinguished Teaching Awards
  • 2011 to 2012 - UQ Summer Research Scholarship
  • 2009 to 2011 - UQ Scholarship for Undergraduate Students

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