The group conducts research into a range of topics on the design and analysis of experiments. Much of the methodological research is motivated by interdisciplinary projects involving scientists and engineers from other areas of academia and industry. The group enjoys regular visits from international collaborators.

The group is actively involved in many meetings and events, with members regularly organising international events and participating in conferences and workshops. The group also organises the MSG Design of Experiments seminar series , joint with statisticians from the University of Manchester.

Active research areas include Bayesian optimal design for complex models, uncertainty quantification, and design optimisation algorithms, with applications from science and technology.

ÍøÂç²ÊƱAPPÏÂÔØ_°Ä¿Í²ÊƱÍø-¹Ù·½ÓÎÏ·, projects are frequently supported and developed through partnerships with manufacturing and pharmaceutical industries, and several government agencies; they often have a strong cross-disciplinary theme.

Recent research highlights include

• Minimax random design with applications to misspecified models (to appear in the Journal of the American Statistical Association)
• An R package for Bayesian optimal design of experiments (published in the Journal of Statistical Software )
• New Bayesian design methods for model derived from ordinary differential equations (published in the Journal of the American Statistical Association ) and models with intractable likelihoods (published in Bayesian Analysis )