Andraž completed his undergraduate and master’s studies in Mathematics and Computer Science at the University of Oxford. He focused mainly on Probability Theory, Stochastic Analysis and Machine Learning. In particular, for his masters’ thesis, he used Generative Adversarial Networks to efficiently generate Lévy area, for the purpose of simulating solutions to Stochastic Differential Equations. In his PhD, he wants to help develop Markov Chain Cubature — a multi-particle alternative to Markov Chain Monte Carlo. Outside of Maths, he enjoys long discussions about Philosophy and Science, loves playing Dungeons & Dragons, and exploring nature.

Supervisor:
James Foster