Samuel Muller has supervised to completion 14 Postdocs, 14 PhDs, 2 Masters of Research students and 13 Honours students. Currently, he supervises 2 Postdocs, 3 PhD students and 4 Masters of Research student.

Discovering, designing and building statistical models that better population and planet health through:

• Variable selection and feature extraction solutions for large and complex data
• Statistical model building for better and more accurate prediction
• Correlated, clustered and complex data analysis
• Classification and improved prediction methods for multiplatform data
• Development of regularization methods for high-dimensional data
• Resampling-based stability information
• Robust selection and estimation methods including when data contains outliers, errors or some of the information is missing
• Analysis of multi-layered and structured data in bioinformatics, microbiome, organ transplant and neuroscience applications

• Industry and government partners are welcome to contact me to explore projects and partnerships that would benefit from the capability of my research group
• Trustworthy data-driven discovery from complex high-dimensional data (Australian Research Council funded, as Lead CI)
• Responsible Statistical Learning: Uncertainty, Fairness and Transparency (Australian Research Council funded, as CI)
• Reliable and accurate statistical solutions for modern complex data (Australian Research Council funded, as CI)
• Cost-Utility Comparison of Down-Titration Strategies for Safer and More Efficient Use of Biologics in Adults with Rheumatoid Arthritis and Psoriatic Arthritis (NHMRC funded, as AI)
• Better Outcomes in Inflammatory Arthritis (NHMRC funded, as AI)