Our statistics consultant, Dr Xia Li, comes to La Trobe with a strong background in Statistics, Computer Science, Medical Science, Biostatistics, Multivariate Statistics, Epidemiology and Public Health.
Xia has expertise in:
- applied statistics
- data mining methods and statistical learning methods
- functional data analysis and wavelet methods in statistics
- longitudinal data analysis and survival data analysis
- modelling (competing risks, multistate, frailty, marginal structure, structural equation and spatial data analysis models)
- Bayesian statistical methods.
Dr Graeme Byrne has over twenty five years experience teaching, researching and consulting in statistics and mathematics. He has broad knowledge of experimental design and analysis with statistical and mathematical consulting experience in the agriculture, health, finance, demography, engineering and energy sectors.
Graeme's main areas of expertise are:
- Experimental design and analysis (e.g. clinical trials, repeated measures and cross sectional designs)
- General linear and mixed model analysis
- Logistic and multinomial regression analysis
- Time series analysis
- Multivariate analysis (e.g. factor analysis and structural equation models)
- Survey design and analysis.
Graeme also has extensive experience working with post graduate research students and assisting La Trobe staff with statistical planning and analysis.
Dr Alysha De Livera is a Senior Lecturer in Statistics in the Department of Mathematical and Physical Sciences. She enjoys research in multidisciplinary, collaborative environments, working closely with scientific investigators from diverse backgrounds. Alysha contributes her statistical expertise to a wide range of problems in medicine, public health, epidemiology, and biology, and conducts research on statistical methods and software to handle issues that are motivated by these studies. She has made contributions to the development of novel statistical methodology and software for the analysis of high-dimensional biological data including metabolomics and single cell data.
Alysha's main areas of expertise are:
- Statistical analysis of large-scale biological data
- Applied statistics
- Meta analysis
- R-based implementations, R package development and R Shiny app development.
Dr Andriy Olenko is an Associate Professor in Statistics in the Department of Mathematical and Physical Sciences. He has published more than 90 papers in international peer-reviewed journals and was a CI on several large European and NATO grants and two ARC discovery projects. He is a cross-disciplinary expert with interests in the areas of statistical and mathematical modelling and data science applications, in particular to medical, signal processing, environmental, cosmology and business problems.
Andriy's areas of expertise are:
- Spatial statistics,
- Time series analytics and forecasting
- Data mining and exploratory data analysis
- Dependent data
- Wavelet analysis
- Mathematical, statistical and R-based implementations
Dr Amanda Shaker is a teaching focussed lecturer in the Department of Mathematical and Physical Sciences, and she also works with the Statistics Consultancy Platform developing and presenting workshops. Amanda’s workshops are interactive and tailored towards non-specialists in statistics. Current workshops include:
- Basic Statistics with R
- Basic Statistics with Stata
- Sample Size Workshop
- Intermediate Statistics with R (under development).
Dr Leila Karimi has particular interests in psychology, health sciences, management and applied statistics. She is an Accredited Statistician with the Statistical Society of Australia, a member of Australian Psychological Society, and an Associate Fellow of Australian College of Health Service Management.
Leila's main areas of expertise are:
- Multivariate analysis
- Multi-level Modelling
- Structural Equation Modelling
- Psychological Measurement
- Partial least square
- Research designs.
Dr Hien Nguyen is a cross-disciplinary expert with primary interest in the areas of computational statistics, data science, machine learning, and artificial intelligence.
His areas of expertise are:
- Online learning, testing, prediction and confidence machines
- Transductive and inductive conformal prediction
- Data mining, knowledge discovery, exploratory data analysis, and explainable AI
- Applied optimisation, mathematical programming, and operations research
- Unsupervised learning, mixture modelling and cluster analysis
- Supervised learning, classification, and discriminant analysis
- Time series and spatial modelling, and learning with dependent data
- Neural networks, deep learning, and AI methods
- Autoencoders, feature selection, feature engineering and dimensionality reduction
- Multivariate data analysis, high dimensional regression, and multiple testing problems
- Predictive analytics and forecasting
- Functional data analysis and manifold data analysis
- R-based implementations and package development.
Contact the Statistics Consultancy Platform:
T: (61) 03 9479 3689