About me
Hello! I am Francesca Panero, Assistant Professor (RTT) in Statistics at the Department of Methods and Models for Economics, Territory and Finance (MEMOTEF) at Sapienza University, Rome, and a Visiting Fellow at the Department of Statistics of the London School of Economics and Political Science where, up until May 2024, I was an Assistant Professor. At LSE, I am also affiliate of the Grantham Research Institute on Climate Change and the Environment.
In 2022 I obtained a PhD in Statistics from the University of Oxford. Before the PhD, I spent quite some time (BSc and MSc) at the Department of Mathematics of the University of Turin and at Collegio Carlo Alberto.
I live in Rome, but you might find me in London too!
You can contact me at francesca [dot] panero [at] uniroma1.it or f [dot] panero [at] lse.ac.uk
News
To all the j-ISBA members out there, I am running for Chair Elect at the elections which will take place this October. j-ISBA (and ISBA) have given me a lot in these years, and with your support I will try to return all this good to make our Bayesian word an even more inclusive place where to foster collaborations and meet great people.
The dates and link for voting will be out soon. Thank you!
Projects
In terms of research, I mostly work on Bayesian models in the following directions: complex networks, disclosure risk assessment (privacy stuff) and Gaussian process modelling. I am also exploring fair machine learning. At the moment, I am working on the following projects:
- Bayesian nonparametric models for sparse networks, in particular networks embedded in a latent space or with dynamic communities. The theorethical framework of these is the graphex, which was introduced (under a different name) by Caron and Fox (2014). I am working on these with F. Caron, J. Rousseau and X. Miscouridou.
- Spatio-temporal Gaussian process models to predict food insecurity at country and regional level. This is joint work with S. Ishida and the UN World Food Programme Hunger Monitoring Unit. This project is supported by a RISF grant by LSE.
- Fair machine learning, in particular models with a ridge penalty to enforce some fairness constraints and how to quantify the uncertainty of the estimators. I am currently working on this with M. Scutari and E. Wit.
On the educational side, I am part of the core team of GENIAL, a focus group at LSE that aims at understanding how students use GenAI tools for learning.
If you are interested in doing a PhD with me, please do get in touch specifying which of my areas of research would be of interest to you.