Post Doctoral Research Associate, University of Bath
Teo has broad interests at the interface of machine learning, differential equations, and probabilistic methods. Prior to joining M4DL he completed a PhD in which he developed deep learning based algorithms to accelerate MCMC for Bayesian inference in models with PDE dependent likelihoods. In his postdoc Teo continues to investigate areas of interactions between machine learning and differential equations. At the moment he is particularly interested in generative modelling techniques based on stochastic differential equations, as well as methods that can allow us to model physically consistent dynamics from data. Teo is passionate about outreach and mathematics communication, as well as promoting equality, diversity, and inclusion within STEM.