Computational Foundations of Data Science

This year’s program features prominent international and domestic academics and researchers, delivering a series of short courses including both lectures and tutorials/labs.

For more information about the Course and/or Lecturer, please click through the link on the respective Course title or Lecturer name.

Bayesian Inference & Data AssimilationIntroduction to Bayesian Computational Methods via Markov Chain Monte Carlo AlgorithmsDr Chris DrovandiQueensland University of Technology
Data Assimilation: A Mathematical IntroductionDr Kody Law
Oak Ridge National Laboratory / University of Tennessee
High-Dimensional StatisticsModel selection and inference for high-dimensional dataDr Davide FerrariThe University of Melbourne
Inverse ProblemsTBCAssociate Professor Youssef MarzoukMassachusetts Institute of Technology
Machine LearningA Decision Making View of Machine LearningDr Hanna KurniawatiThe University of Queensland
Martingales, McDiarmid and Machine Learning: How to validate models like a pro!Dr Brendan van RooyenQueensland University of Technology
Nonlinear OptimisationOptimisation Techniques For Data AnalysisProfessor Stephen WrightUniversity of Wisconsin-Madison
Numerical Linear AlgebraLarge Scale Matrix ProblemsDr Linda StalsAustralian National University