Department of Statistics
University of Oxford
24-29 St Giles'
Oxford OX1 3LB
I work on large language models safety with Dr Owain Evans. I am broadly interested in technical and policy approaches to address the societal impact of AI.
I have recently defended my PhD in Statistics and Machine Learning at the University of Oxford, during which I mostly worked on inference for generative models, spanning Bayesian simulation-based inference and training methods for generative neural networks. Some of the approaches I developed build on concepts from probabilistic forecasting. My supervisors were Prof. Ritabrata Dutta (Uni. Warwick) and Prof. Geoff Nicholls (Uni. Oxford). I was also interested in conformal prediction, normalizing flows, gradient-based MCMC methods and weather forecasting.
Prior to my PhD studies, I obtained a Bachelor’s degree in Physical Engineering from Politecnico di Torino (Italy). Afterwards, I studied towards an MSc in Physics of Complex Systems awarded by Politecnico di Torino and Université Paris-Sud, France. I have carried out my MSc thesis at LightOn, a machine learning startup in Paris.
|Dec 20, 2022||I won a travel award at the International Conference for Statistics and Data Science by the Institute of Mathematical Statistics. I really enjoyed the opportunity to present my work there!|
|Nov 17, 2022||On the 9th of November, I successfully defended my PhD thesis . A profound thanks to my examiners Chris Holmes and Chris Oates for their insightful comments and suggestions.|
|Jun 3, 2022||I have two preprints on arXiv exploring an alternative to adversarial training to train generative networks; the first applies it to probabilistic forecasting, while the second is concerned with Likelihood-Free Inference. I feel that is a promising overlooked approach. Happy to hear any feedback!|
|Mar 16, 2022||I have created a website aimed at listing works on using Neural Networks in Bayesian Likelihood-Free Inference I have added the papers I am aware of, but please contribute others you may know (see “About” page for how).|
|Feb 3, 2022||Our paper discussing a new method for learning summary statistics for Approximate Bayesian Computation has been published in Journal of Machine Learning Research!|