Georgios research interests are in Bayesian statistics and statistical
computing. He works on the design of Bayesian methods for uncertainty
quantification, calibration, and prediction of large computer models or
complex systems, as well as on the development of stochastic simulation
methods such as Markov chain Monte Carlo, and stochastic optimisation.
Applications involve, carbon-capture, and climate modelling.