Victoria Volodina

About me

I am a Research Associate at the Alan Turing Institute at London. I work as part of the MUGM (Managing Uncertainty for Government Models) project. My current research is on developing innovative mathematical methods for quantifying uncertainty in government models.

I have received my PhD in Mathematics from the University of Exeter, where I was supervised by Dr Daniel Williamson. My thesis titled Uncertainty Quantification for complex computer models with nonstationary output. Bayesian optimal design for iterative refocussing.

Publications

Preprints

1. Victoria Volodina, Nikki Sonenberg, Edward Wheatcroft and Henry Wynn (2020). Majorisation as a theory for uncertainty. arXiv:2007.10725.
2. Victoria Volodina, Edward Wheatcroft and Henry Wynn (2020). Cheap, robust and low carbon: comparing district heating scenarios using stochastic ordering. arXiv:2003.04170

Journal articles

1. Victoria Volodina and Daniel B. Williamson (2020). Nonstationary Gaussian Process Emulators with Kernel Mixtures. SIAM/ASA Journal on Uncertainty Quantification

Contact

Email: vvolodina@turing.ac.uk