Staff Profile

I joined the school as a Lecturer in Statistics in May 2024. Before that I had the following positions:

• Postdoctoral researcher, Department of Statistical Science, University College London, 2022-24
• Postdoctoral researcher, Department of Statistics, University of Warwick, 2020-22

I obtained my PhD from the Mathematics and Statistics Doctoral Training Centre (MASDOC) at the University of Warwick in 2020.

My interest lies at the intersection between Applied Probability and Statistics, with a particular focus on theory and methodology for Markov Chain Monte Carlo (MCMC). More specifically, I have been working on:

Probability theory: Stability and convergence of Markov processes, Piecewise Deterministic Markov Processes, Poisson processes, Locally balanced jump processes.

Computational Statistics: Approximate Bayesian Computation, Pseudo-marginal MCMC, methodology for Piecewise Deterministic Monte Carlo, methodology for Locally Balanced Monte Carlo.

2024/2025: Bayesian Inference (MAS3902)

• Articles

  • Livingstone,S,Nusken,N,Vasdekis,G,Zhang,RY. Skew-symmetric schemes for stochastic differential equations with non-Lipschitz drift: an unadjusted Barker algorithm. 2024. Submitted.
  • Vasdekis G, Roberts GO. Speed Up Zig-Zag. Annals of Applied Probability 2023, 33(6A), 4693-4746.
  • Watson JW, Boyd R, Dutta R, Vasdekis G, Walker ND, Roy S, Everitt R, Hyder K, Sibly R. Incorporating environmental variability in a spatially-explicit individual-based model of European sea bass. Ecological Modelling 2022, 466, 109878.
  • Vasdekis G, Roberts GO. A note on the polynomial ergodicity of the one-dimensional Zig-Zag process. Journal of Applied Probability 2022, 59(3), 895-903.

• Conference Proceedings (inc. Abstract)

  • Vasdekis G, Roberts GO. Speeding up the Zig-Zag process. In: International Conference on Bayesian Statistics in Action BAYSM 2022. 2023, Montréal, Canada: Springer.