I am a first year PhD student and junior researcher in Bayesian computation under the supervision of Prof. Krysztof Latuszynski and Prof. Gareth Roberts. My goal is to contribute to the development of computational methodology that enables exact Bayesian inference for complex inference problems in the sciences and AI. I also bring an applied perspective to my work due to my background in Economics and my industry experience as a Data Scientist. That perspective informs my interest in translating methodological research into plug-and-play tools that are accessible to applied researchers.
Areas of research
- Monte Carlo sampling methods for intractable targets, e.g. diffusion paths and intractable likelihoods.
- Bayesian data integration for spatio-temporal inference problems, e.g. election forecasting and real estate pricing.
J. Garcia Montalvo, O. Papaspiliopoulos and T. Stumpf-Fetizon, Bayesian forecasting of electoral outcomes with new parties’ competition, European Journal of Political Economy, 2019. doi: 10.1016/j.ejpoleco.2019.01.006
ST404 Applied Statistical Modelling (T2 2018-19)
17DS04 Bayesian Machine Learning in Social Sciences (Barcelona GSE, T3 2016-17)
14D001 Statistical Modelling and Inference (Barcelona GSE, T2 2016-17)