Our People

Profile: La Trobe Scholar, Google Scholar

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. Dr Xia Li's principal research interests are applied statistics, biostatistics, especially longitudinal data analysis, survival data analysis, latent-based models, data mining methods and statistical learning methods with expertise in data analysis and statistics modelling. She is proficient in a variety of data analysis and statistical software packages. Dr. Li has published over 170 research papers in peer-reviewed journals. Xia also collaborates with researchers from various disciplines both within and outside La Trobe University.

Xia has expertise in:

• Experimental design and sample size calculations
• Applied statistics
• Data mining methods and statistical learning methods
• Functional data analysis and wavelet methods in statistics
• Longitudinal data analysis
• Survival data analysis
• Multivariate statistical modelling (multistate, marginal structure, structural equation and spatial data analysis models)

Profile: La Trobe Scholar, Google Scholar

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 was a former co-chair of the Biostatistics and Bioinformatics Section of the Statistical Society of Australia (SSA), helps promote the discipline of Statistics and Data Science in Australia, and advocates women in STEM. Alysha, with her extensive experience in mathematical statistics, biostatistics, bioinformatics and data science, is passionate about building capacity to improve the quality and impact of La Trobe’s research.

Alysha's main areas of expertise are:

• Biostatistics
• Statistical analysis of large-scale biological data
• Applied statistics
• Meta analysis
• R-based implementations, R package development and R Shiny app development.

Profile: La Trobe Scholar

Dr Graeme Byrne has over 30 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 students.

Profile: La Trobe Scholar, Google Scholar

Dr Hien Nguyen is a cross-disciplinary expert with a 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

Profile: La Trobe Scholar, Google Scholar, Google Profile

Dr Andriy Olenko (https://sites.google.com/site/olenkoandriy/) 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

Profile: La Trobe Scholar, Google Scholar

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: Regression Analysis