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Dr Christopher Drovandi

Science and Engineering Faculty,
Mathematical Sciences,
Statistical Science

Personal

Name
Dr Christopher Drovandi
Position(s)
Senior Research Fellow (DECRA)
Science and Engineering Faculty,
Mathematical Sciences,
Statistical Science
Senior Lecturer
Science and Engineering Faculty,
Mathematical Sciences,
Statistical Science
Discipline *
Statistics
Phone
+61 7 3138 1756
Fax
+61 7 3138 2310
Email
Location
View location details (QUT staff and student access only)
Identifiers and profiles
ORCID iD Twitter LinkedIn
Qualifications

PhD(Statistics) (Queensland University of Technology), BAppSc(Statistics) (Queensland University of Technology), BInfTech(SoftwareEng/DataComms) (Queensland University of Technology)

Professional memberships
and associations
Keywords

Approximate Bayesian Computation, Markov chain Monte Carlo, Sequential Monte Carlo, Statistics

* Field of Research code, Australian and New Zealand Standard Research Classification (ANZSRC), 2008

Biography

Dr Chris Drovandi is a Senior Lecturer in the School of Mathematical Sciences at the Queensland University of Technology (QUT) and is an Associate Investigator of ACEMS.  Chris completed his PhD in 2012 at QUT and is currently a holder of an Australian Research Council Discovery Early Career Researcher’s Award, delivering close to $400,000 in funding over 3 years.

His research interests are in Bayesian algorithms for complex models, optimal Bayesian experimental design methods and the translation of Bayesian methods across many disciplines.  Chris is currently supervising several post-graduate students.

For more information, visit Dr Drovandi’s website.

This information has been contributed by Dr Christopher Drovandi.

Teaching

Achievements in Teaching

  • 2017 AMSI Winter School lecturer by invitation (Queensland University of Technology)
  • 2015 AMSI Summer School lecturer by invitation (University of Newcastle)
  • Nominated for 2015 QUT Vice-Chancellor’s Award for Excellence in Teaching
  • Nominated for 2014 QUT Science and Engineering Faculty Award for Excellence in Postgraduate Research Supervision
Postgraduate Teaching
Computational Bayesian Statistics
  • Monte Carlo Integration
  • Importance Sampling and Adaptive Importance Sampling
  • Markov chain Monte Carlo
  • Sequential Monte Carlo
  • Approximate Bayesian Computation
Undergraduate Teaching
Current:
  • Generating Functions
  • Transformation of Random Variables
  • Order Statistics
  • Markov Chains including Simple Random Walks and Branching Processes
  • Continuous Time Markov Chains
  • Brownian Motion
Previous:  
  • Probability
  • Univariate Discrete and Continuous Random Variables
  • Bivariate Discrete Distributions
  • Chi-square Goodness-of-fit
  • Markov Chains
  • Poisson Processes
  • Random Number Generation
  • Rejection Sampling
  • Importance Sampling
  • Monte Carlo Integration
  • Normal regression
  • Poisson and binomial regression
  • Multinomial regression
  • log-linear models
  • R Programming
This information has been contributed by Dr Christopher Drovandi.

Publications


For more publications by this staff member, visit QUT ePrints, the University's research repository.

Awards

Awards and recognition

Type
Academic Honours, Prestigious Awards or Prizes
Reference year
2016
Details
Vice-Chancellor's Performance Fund Award (for excellence in Research)
Type
Academic Honours, Prestigious Awards or Prizes
Reference year
2012
Details
The ISBA Lifetime Members Junior Researcher Award

Research projects

Grants and projects (Category 1: Australian Competitive Grants only)

Title
Tractable Bayesian Algorithms for Intractable Bayesian Problems
Primary fund type
CAT 1 - Australian Competitive Grant
Project ID
DE160100741
Start year
2016
Keywords

Supervision