Nicola Branchini
Research Fellow in the Department of Statistics at the University of Warwick, working with Gareth Roberts under the ProbAI Hub
Hello! I am a Research Fellow in the Department of Statistics at the University of Warwick, working with Gareth Roberts under the ProbAI Hub. Sometimes I blog as well here.
Previously, I was a PhD student in Statistics in the School of Mathematics at the University of Edinburgh, advised by Víctor Elvira, and an ELLIS PhD student co-advised by Aki Vehtari at Aalto University.
My real interests are broad, spanning computational statistics and statistical/probabilistic machine learning, with a focus on methodology. For my PhD, I have been focussing on developing methodology in Monte Carlo.
A sample of some specific interests:
- Importance sampling – The concept of IS underpins most computational methods where the interest is in a consistent estimator of a quantity of interest. I'm interested in all kinds of aspects of IS, such as dimension scaling, good choices of proposal densities, robustness to inexact function evaluations, and practical diagnostics.
- Bayesian cross-validation – The Bayesian counterpart to classical cross-validation presents an interesting setup for IS and computational methods, and I'm interested in extensions and theory around Bayesian CV.
- Heavy tails – Approximating distributions with heavy tails is challenging and still a very active research area. I'm also interested in using concepts from heavy tails to understand the properties of MC estimators.
- …and adjacent ideas – I like continuosly learning new concepts from neighbouring fields. There are so many interesting ideas still to explore!
Please do not hesitate to contact me for talking about research.
- Very excited to join (soon) the University of Warwick as a ProbAI research fellow, where I will work with Gareth Roberts.
- Three new papers in 2026: How to approximate inference with subtractive mixture models (AISTATS 2026), On the bias of variational resampling (AISTATS 2026), and Multimarginal Flow Matching with Adversarially Learnt Interpolants (ICLR 2026). See more details on the publications page.
- Our conference paper Towards Adaptive Self-Normalized Importance Samplers is accepted at the Statistical Signal Processing Workshop (SSP), 2025.✰
- Thanks to the Institute for Mathematical and Statistical Innovation (IMSI) for generously awarding me a travel grant of 1000 US dollars to attend MCM 2025 in Chicago !
- Thanks to G-Research for generously awarding me a grant so that I will be able to attend NeurIPS in Vancouver
- Excited (and a bit stressed) to give a talk at the 6th workshop on Sequential Monte Carlo (SMC 2024). ✰
- Adaptive importance sampling for heavy-tailed distributions via alpha-divergence minimization to appear in AISTATS 2024. ✰
- Variational resampling to appear in AISTATS 2024. ✰
- Causal Optimal Transport of Abstractions to appear in CLEaR (Conference on Causal Learning and Reasoning) 2024. ✰
- Contributed talk accepted in a minisymposium at the 14th international conference on Monte Carlo methods and applications (MCM) 2023, on "Generalized Self Normalized Importance Sampling". ✰
- Causal Entropy Optimization to appear in AISTATS 2023. ✰
- Received ISBA Travel Award for BayesComp 2023.
- Accepted for attending the 2023 Probabilistic Numerics School in Tübingen
- Poster on "Generalized Self Normalized Importance Sampling" accepted at BayesComp 2023.
- I received the Turing Enrichment Scheme (Placement Award, for 6 months) offer.
Journals
Statistics and Computing, Transactions on Machine Learning Research, Statistics and Probability Letters
Conferences & Workshops
AISTATS 2023, AABI (workshop) 2023, NeurIPS 2023, ICLR 2024, AISTATS 2024, NeurIPS workshop on Bayesian decision-making and uncertainty 2024, AISTATS 2025