Scholar
Ryan Thompson
Google Scholar ID: rQx30dcAAAAJ
University of Technology Sydney
Citations & Impact
Citations
64
H-index
5
i10-index
2
Publications
10
Co-authors
8
list available
Publications
Resume (English only)
Academic Achievements
- ProDAG: Projected variational inference for directed acyclic graphs. Advances in Neural Information Processing Systems, 2025.
- Scalable subset selection in linear mixed models. arXiv, 2025.
- Semi-supervised Gaussian mixture modelling with a missing data mechanism in R. Australian and New Zealand Journal of Statistics, 2024.
- Contextual directed acyclic graphs. International Conference on Artificial Intelligence and Statistics, 2024.
- Familial inference: Tests for hypotheses on a family of centres. Biometrika, 2024.
- Flexible global forecast combinations. Omega, 2024.
- Group selection and shrinkage: Structured sparsity for semiparametric additive models. Journal of Computational and Graphical Statistics, 2024.
- The contextual lasso: Sparse linear models via deep neural networks. Advances in Neural Information Processing Systems, 2023.
- Robust subset selection. Computational Statistics and Data Analysis, 2022.
- Optimal selection of expert forecasts with integer programming. Omega, 2018.
Research Experience
- Currently a Research Fellow at the University of Technology Sydney and a Visiting Scientist at CSIRO’s Data61. Worked at KPMG, advising financial institutions on quantitative risk management.
Education
- Ph.D. from Monash University; Undergraduate from the University of Sydney; Previously a Research Associate at the University of New South Wales.
Background
- Research Interests: Causal discovery, high-dimensional learning, Bayesian inference. Professional field: Machine learning, particularly in developing new techniques for complex data that are statistically principled, computationally scalable, and operationally trustworthy.
