Statistics and Data Science

Bayesian Inference

• Time-series analysis, streaming data
• Robust statistics, inverse regression
• Scalable algorithms (Big Bayes)

Decision Theory & Optimisation

• Adaptive utility, sequential decision-making
• Lightweight and private optimisation

Machine Learning

• Linear & Logistic Regression
• Support Vector Machines & Kernel Methods
• k-Means Clustering and Mixture Models for Unsupervised Learning
• Neural Networks
• Deep Learning

Data Visualisation

• Visual Information – perception and understanding
• Graph, Spatial and Interactive data visualisation

Sample Application Areas

• Ecology, astronomy
• Vision/video
• Social networks
• Health
• Fintech
• Education

Faculty Members

Click on the staff member's name to view their full profile and publications. 

Staff Name Research Group & Centres	Research Interests	Publications
Benavoli, Alessio	Bayesian statistics, probabilistic machine learning
Brophy, Caroline	Statistical modelling of non-standard situations, such as ecology, biodiversity, agronomy
D'Angelo, Silvia	Statistics and Information Systems
Georgiadis, Athanasios	Nonparametric statistics, Spatial statistics, Bayesian statistics,  Mathematics.
Howard, Emma	Statistics education, clustering analysis, applied statistics, and learning analytics.
Ng, Tin Lok James	Network Analysis, Mixture Model, Bayesian statistics, Spatial Statistics
White, Arthur ADAPT	Computational statistics, applied statistics, model-based clustering, pharmacoeconomics.
Wilson, Simon INSIGHT, ADAPT	Bayesian statistics, statistical reliability, interface of information and communications systems and statistical learning, computationally intensive statistics
Wyse, Jason ADAPT	Latent Gaussian models, Model-based clustering, Bayesian methods, Bayesian model determination, block modelling, changepoint models, application-based model development
Zhang, Mimi	Stochastic Modelling, Markov Decision Process, Multivariate Modelling, Data Mining