I am an NLP Researcher, and Quant at G-Research.
Before that, I did my PhD at Sorbonne Université, while being a Research Engineer at BNP Paribas. My PhD, Deep Learning for Data-to-Text Generation was done under the supervision of Patrick Gallinari and Laure Soulier, from the MLIA team. All projects (solos & duos) are available on Github and ArXiv.
I work as a Quant Researcher, meaning I research systematic trading ideas to predict the future of financial markets, applying scientific techniques to find patterns in large, noisy and rapidly changing realworld data sets. In otherwords, I apply and develop state-of-the-art NLP approaches (read transformers) to find trading signals in large textual corpora. By making computers do the trading, we remove human error and make sure only rigourously proven-to-work strategies are deployed.
Right now, I am interested in all things NLP:
- Learning representations & embeddings of sentence, entity, etc
- Large Language Models
Before that, I was a Research Engineer at BNP Paribas. In practice, I bridged the gap between research/academia and applications/enterprise, being part of the team which developped the internal company-wide search engine, as well as a number of other tools (translation plateform, document NLP, etc.).
During my PhD, I worked on Data-to-Text Generation (DTG), i.e. building systems able to:
- comprehend complex structured data (e.g. tables, graphs, etc.);
- produce a fitting description (from one sentence to several paragraphs).
My PhD work has been focused on a critical aspect of DTG: ensuring factualness in system outputs.
On a personal note, I am a climbing enthusiast and try to swim at least once per week. I greatly enjoy storytelling, both reading and going to the movies (used to go twice a week w/ movie pass before I moved to London). I’m also a fan of cooking: meals, deserts, as well as cocktails 🍹 See the Gallery Section for some proof that I go outside!