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Vladislav Vyshemirsky is a Lecturer in the School of Mathematics and Statistics at the University of Glasgow, specializing in the fields of Bayesian modelling and computational statistics. He is actively engaged in research that focuses on developing emulation methods to enhance inference performance in complex models. His work primarily revolves around Bayesian experiment design, model comparison, and approximate Bayesian inference, particularly in the context of continuous time Markov chain models. In addition to his research, Vladislav teaches Bayesian Statistics courses at both undergraduate and master's levels, including an online MSc programme in Bayesian Computation. He is committed to advancing the understanding of uncertainty assessment in statistical analysis and educating the next generation of statisticians.