Statistics and Data Science

Developing and applying statistical inference, decision theory & optimisation, machine learning and visualisation techniques that will process data and draw new insights and knowledge from the data.

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

Faculty Members

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

Staff Name Research Group & Centres Research Interests
Benavoli, Alessio Bayesian statistics, probabilistic machine learning
Brophy, Caroline Statistical modelling of non-standard situations, such as ecology, biodiversity, agronomy
Georgiadis, Athanasios

Nonparametric statistics, Spatial statistics, Bayesian statistics,  Mathematics.

Keaney, Aideen User perceptions of social networking sites. Trust and privacy as they relate to technology. Online identity theft
Ng, Tin Lok James Network Analysis, Mixture Model, Bayesian statistics, Spatial Statistics

White, Arthur


Computational statistics, applied statistics, model-based clustering, pharmacoeconomics.
Wilson, Simon
Bayesian statistics, statistical reliability, interface of information and communications systems and statistical learning, computationally intensive statistics

Wyse, Jason


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