Charlotte Jamotton

Charlotte Jamotton

Postdoctoral researcher in actuarial science at UQÀM

Posts by Collection

portfolio

publications

FairGGPR: a multi-criteria fair Gaussian regressor for insurance pricing

Published in , 2026

This article develops a Bayesian non-parametric regression framework for insurance pricing that incorporates several fairness interventions within a single predictive model.

Recommended citation: Jamotton, C., & Hainaut, D. (2026). "FairGGPR: A Multi-Criteria Fair Gaussian Regressor for Insurance Pricing." Manuscript under revision.

talks

Insurance analytics with clustering techniques

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This was my first conference presentation, just four months into my PhD. I attended PARTY alongside my former colleagues Vanessa Hannah and Keivan Diakite. It was also where I first met members of the KU Leuven team. I presented my first research talk on clustering methods for heterogeneous insurance datasets and received the Best Presentation IAALS Prize. PARTY is a workshop organised every two years by Séverine Arnold (UNIL) and Corina Constantinescu (University of Liverpool), bringing together young researchers working on actuarial risk.

Insurance analytics with clustering techniques

Published:

My second conference presentation, this time back home in Belgium. I presented my work to colleagues and professors from my department, as well as researchers from UNamur. It was a nice opportunity to share my research with a slightly different audience and to present how clustering methods can be used to explore structure and heterogeneity in insurance portfolios.

Insurance analytics with clustering techniques

Published:

Ten months into my PhD, this was my first presentation in front of a truly international audience (a little more academic pressure). I travelled to Edinburgh with Rodrigue Kazzi, who actually submitted the final version of his PhD thesis at the airport when we landed!

Variational AutoEncoder for synthetic insurance data

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About a year into my PhD, I presented my second PhD project for the first time at the Young Researcher Day organised by my department at UCLouvain. The event is a great opportunity to share our research with fellow colleagues in a more friendly atmosphere. I have particularly good memories of this presentation — it was probably the first time I really felt confident presenting my work. I introduced my new project on generating synthetic insurance data, which is also where my interest in Bayesian statistics really started to grow.

Variational AutoEncoder for synthetic insurance data

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This was another opportunity to present my work on synthetic insurance data to a broader data science audience. It was also nice to step a little outside the usual actuarial crowd and discuss how statistical and machine learning methods can be used to generate realistic synthetic insurance datasets.

Variational AutoEncoder for synthetic insurance data

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One of my favourite conferences during my PhD! The Insurance Data Science Conference brings together two parallel perspectives, with an academic track and an industry track, which made it especially interesting to meet and exchange with people working in insurance outside academia. I really enjoyed the mix of research and industry discussions, and Stockholm itself was definitely a highlight — I may have slightly fallen for the Stockholm archipelago! I don’t have any photos from the conference itself, but I have plenty from the weekend kayaking trip around the archipelago afterwards.

A multivariate Energy-based fairness adjuster for premiums

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This was the first time I presented my work on fairness in insurance pricing — a project I had started towards the end of my second year of PhD and that turned out to be quite a challenging one to get into! I initially explored causal approaches before eventually focusing on demographic parity. I was not feeling particularly confident about this presentation, and my slides were… very much a work in progress.

It was also an important one for my PhD journey. This was where I first met Marie-Pier Côté, whose work on fairness with Arthur Charpentier and Olivier Côté had a major influence on my research over the following two years. Marie-Pier later joined my thesis committee, and I eventually started my postdoc with Arthur!

The workshop was organised by the KU Leuven team as part of the EoS project that funded my research. I travelled there with my colleague and close friend Patricia Ortega Jimenez. We almost missed our train and spent most of the journey, and then the walk from the station to the workshop room, stressing about our presentations.

Variational AutoEncoder for synthetic insurance data

Published:

Probably the most memorable conference of my PhD.

PARTY is a workshop, organized by Séverine Arnold (UNIL) and Corina Constantinescu (University of Liverpool), that takes place every two years and has a rather special format. Unlike a typical conference where you might attend a selection of talks and spend the rest of the time moving between sessions, PARTY is designed to bring everyone together. We attend each other’s talks, and spend a lot of time interacting outside the formal programme. For a few days, you are essentially placed in a little academic bubble with the same group of people 24/7 — with the slightly ambitious goal of bringing everyone, and hopefully their brain cells, a little closer together. It creates a really unique atmosphere: you get to know people’s research in much more depth, but also get to know the people behind it.

PARTY became even more special because of the people I met along the way. The previous edition was actually my first PARTY — and my very first conference — where I met Paul and Rodrigue. Two years later, in Liverpool, this was where I met Dries, Emilio, Gayani (in that church-turned-pub), Mélanie, and Olivier (and his camera capturing memories). They all became some of the friendliest and most familiar faces I would look forward to seeing at conferences.

Liverpool felt like the beginning of a very good chapter.

A multivariate Energy-based fairness adjuster for premiums

Published:

Back to IDS, this time in London! This was probably my favourite session I have ever been part of, presenting my work on fairness alongside Marie-Pier Côté and Mathias Lindholm. It was a great opportunity to exchange ideas with two researchers whose work I really enjoyed, and the discussion during the session was particularly memorable. Katrien Antonio captured the moment perfectly with a photo of the three of us afterwards!

Outside the conference, I also managed to squeeze in a 30km bike ride around London with Dries, which turned it into my favourite London trip.

A multivariate Energy-based fairness adjuster for premiums

Published:

A very special one to close this conference season: the whole KU Leuven team was there! The conference itself was top tier — Tartu’s university campus is seriously impressive (let’s just not talk about the mosquitoes).

FairGGPR: A multi-criteria fair Gaussian regressor for insurance pricing

Published:

Back to the Young Researcher Day at UCLouvain, almost exactly two years after presenting my second PhD project there for the first time. This time, I presented my final PhD project: FairGGPR, a multi-criteria fair Gaussian regressor for insurance pricing. It was also the first time I introduced its unofficial nickname, the Pesh Mel’ Bush model.

It was a nice full-circle moment to come back to the YRD with the project that would eventually become the last piece of my PhD thesis, and to see how much things had happily changed since my first presentation there two years earlier.

FairGGPR: A multi-criteria fair Gaussian regressor for insurance pricing

Published:

My first seminar! I was invited by Peter Hieber — after failing to keep my promise to stop by Lausanne during my summer trek through France, Italy, and Switzerland — to present my work on fairness in insurance pricing at the Actuarial Seminar at the University of Lausanne. The project was still in its early stages at the time, so it was also a fun opportunity to share some ideas that were very much still taking shape. It was a nice change from conferences and workshops, with a bit more time to dive into the research and discuss it properly.

FairGGPR: A multi-criteria fair Gaussian regressor for insurance pricing

Published:

A bit of a full-circle moment! This time, the ASTeRISK EOS Workshop was held at UCLouvain,co-organised with my PhD supervisor, Prof. Donatien Hainaut. We invited Mathias Lindholm (Stockholm University) and Yevhen Havrylenko (UNIL), and of course had the KU Leuven team back with us as well. It was really nice to see everyone together in Louvain-la-Neuve after all the workshops, and conferences over the previous years.

I also presented my work on FairGGPR and ended the day at the pub so the team could try the Pesh Mel’ Bush.

A multivariate Energy-based fairness adjuster for premiums Permalink

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Back to Stockholm, and back to my first research project on fairness — this time presenting it after its publication in the North American Actuarial Journal. This was probably my best presentation to date. It was also my first conference with my PhD supervisor, Prof. Donatien Hainaut!

The timing made it even more special: this was just two weeks after my private PhD defence on 28 May, so it felt a little like the beginning of the next chapter. And of course, no trip to Stockholm would be complete without some time in the archipelago — got to experience Midsommar in a cabin afterwards.

Non-life insurance analytics

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On 20 August 2026, I publicly defended my PhD thesis in actuarial science at UCLouvain. My thesis explored statistical and machine learning methods for non-life insurance, with a particular focus on Bayesian modelling, predictive uncertainty, fairness, and interpretability.

FairGGPR: A multi-criteria fair Gaussian regressor for insurance pricing

Published:

First presentation of my postdoc! After defending my PhD on 20 August and arriving in Montréal two weeks later, I gave my first one-hour research seminar at Concordia University as part of the CANSSI Quebec Postdoc Day. I had the chance to meet other postdoctoral researchers along the way. It was also the first time I had the opportunity to properly present the Bayesian mathematics behind FairGGPR, rather than having to compress the methodology into a few slides and move on to the results.

The whole UQÀM team also came to attend my talk. I’ve always valued this kind of thing in research groups — showing up for each other — and it made me especially happy to find that spirit at UQÀM.

FairGGPR: A multi-criteria fair Gaussian regressor for insurance pricing Permalink

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My second seminar in Montréal! I was invited to present FairGGPR at the CRM Applied Mathematics Seminar at McGill University. I gave more or less the same talk I had presented at Concordia two weeks earlier, but this time I went a little deeper into the mathematical side of things.

I got a really interesting comment about the error coming from the Laplace approximation. That approximation error could potentially propagate through the rest of the model and affect the interpretation of the impact of different fairness interventions on the final predictions and uncertainty — definitely something I need to look into!

The seminar also happened right after Daniela Witten’s seminar conference dinner — so many ideas I enjoyed, plus pink slides and a Taylor Swift reference! Looking forward to the upcoming Written by Witten column.

Marie-Pier’s whole PhD team had also come down from Québec, so it was really nice to meet everyone and see Olivier again (and thanks to them for attending my seminar as well!).

teaching

Statistique approfondie

Bachelor course, UCLouvain, Faculté des sciences (SC), 2022

Main topics

  • Statistical inference
  • Estimation and hypothesis testing
  • Regression methods
  • Statistical modelling
  • Data analysis and interpretation

My role

I prepared and led exercise sessions, worked through statistical problems with students, and helped them develop the intuition needed to move from statistical theory to practical data analysis.

Introduction à la programmation (R, SAS, Python)

Bachelor course, UCLouvain, Faculté des sciences (SC), 2022

Tools

  • R
  • Python
  • SAS
  • JMP
  • SPSS

Main topics

  • Programming fundamentals
  • Data manipulation and analysis
  • Statistical computing
  • Data visualisation
  • Applying statistical methods through code
  • Working with real datasets

My role

I guided students through practical exercises, and helped troubleshoot their code.

Valorisation financière des engagements actuariels

Master course, UCLouvain, Faculté des sciences (SC), 2024

Main topics

  • Financial mathematics and interest-rate modelling
  • Option pricing
  • Black–Scholes models
  • Stochastic calculus
  • Numerical methods for actuarial valuation
  • Applications to actuarial liabilities

My role

My role focused on preparing and teaching exercise sessions, guiding students through problem-solving, answering questions, and helping bridge the gap between the theoretical material covered in lectures and its practical application.