| Oct 15, 2024 | We have two new preprints on arXiv! One on predicting the performance of LLMs on individual instances, the other one on predicting the answers of LLM benchmarks from simple features. |
| Oct 01, 2024 | I have obtained a grant from Open Philanthropy on building a benchmark for measuring the ability of LLMs to perform data science tasks! 🤓 📊 |
| Sep 21, 2024 | Our paper Generalised Bayesian Likelihood-Free Inference (on which I worked during my PhD studies) is now published at the Electronic Journal of Statistics!  |
| Apr 17, 2024 | We’ve launched academicjobsitaly.com, a portal to search academic jobs in Italy, boasting automated notifications for new openings! 🇮🇹 |
| Mar 05, 2024 | Our paper introducing a method to train generative networks for probabilistic forecasting using scoring rules has been published in Journal of Machine Learning Research!  |
| Feb 01, 2024 | I co-authored an op-ed on the OECD.AI policy website about how an exemption for “therapeutic purposes” in the EU AI Act could serve as a loophole. |
| Jan 16, 2024 | Our paper How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions has been accepted at ICLR 2024! |
| Aug 01, 2023 | I am happy to communicate that I will join the Leverhulme Centre for the Future of Intelligence at the University of Cambridge in October 2023  |
| Jul 15, 2023 | Today, I formally graduated from my PhD at Oxford! |
| 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 03, 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 03, 2022 | Our paper discussing a new method for learning summary statistics for Approximate Bayesian Computation has been published in Journal of Machine Learning Research! |
| Dec 04, 2021 | Our paper describing the likelihood-free inference package ABCpy has been published in the Journal of Statistical Software! Check here for a quick YouTube video introducing the library. |
| Aug 12, 2021 | Our optimal lockdown paper has finally been published by PLOS Computational Biology! Check the media coverage here! |
| Jul 06, 2021 | If you missed my contributed talk on my work on “Generalized Bayesian likelihood-free inference using scoring rules estimators” at ISBA 2021 World Meeting, you can find the pre-recorded video here on YouTube. |
| Apr 09, 2021 | I’ve just released a preprint on Generalized Bayesian Likelihood-Free Inference using Scoring rules with pseudo-marginal MCMC. We believe it is a promising bridge between these two lines of research. Preliminary version, feedback is welcome! |
| Feb 11, 2021 | Our methodological paper on designing an optimal lockdown considering an epidemiological model has been accepted for publication by PLOS Computational Biology! |
| Dec 09, 2020 | Our paper describing the likelihood-free inference package ABCpy has been accepted for publication in the Journal of Statistical Software! |