CV

For a more comprehensive overview : LinkedIn

Research experience

• Postdoctoral fellow (2024-present)
  • Université de Lorraine, LORIA (CNRS)
  • Topic models, interpretble representations, mono and multidocument summarization
• PhD Candidate (2020-2023) and Teaching and Research Fellow (2023-2024)
  • Université du Mans
  • Sparse and interpretable embeddings methods based on graphs
• Research Intern (Jan.-Jul. 2020)
  • Université du Mans
  • Graph-based word embedding methods
  • Supervisor: Nicolas Dugué
• Research Intern (Apr.-Jul. 2019)
  • Université du Mans
  • Unsupervised keyword extraction from document of the SNCF prescript
  • Supervisor: Nicolas Dugué
• Business Intelligence Intern (Apr.-Aug. 2018)
  • Ambacia Consulting
  • Build data analysis dashboards from Insurrance Company data

Education

• PhD in Computer Science, Université du Mans, 2024
• MSc in Computer Science (NLP), Université du Mans, 2020
• BSc in Computer Science, Université de Tours, 2018
• Erasmus Exchange, HAW Hamburg, 2016-2017

Languages

• Languages
  • French : native
  • English : billingual
  • German : working proficiency

Publications

Awards and grants

• Frontier Prize - Best Paper 2021
  • Frontier prize for the best communication of the 2021 symposium on intelligent data analysis (IDA) Sponsored by KNIME.
• RFI Atlanstic 2020 - Grant
  • Grant awarded by the Pays de la Loire region through RFI Atlanstic 2020 to attend the 6th IVADO/MILA Deep Learning School.

Dissemination

• MAIF conference on AI 2022
  • Presentation of neural methods to the public through a demonstration related to object recognition.
• European Researcher’s Night & Fête de la Science 2021
  • Université du Mans
  • Production of a demonstrator around computer vision able to detect and segment objects in a video stream using artificial intelligence. Edition of a poster to explain the basic principles of deep learning and exchange with the public about ethical and environmental considerations of these approaches.

Projects

• SNCF domain-specific word embeddings, 2019-2020
  • Université du Mans
  • Supervised classification of documents using word embeddings from general language and learnt on domain-specific documents. Evaluation of the impact of the word representation on the classification of technical documents.
• MMA Customer Surveys, 2018-2019
  • Université du Mans
  • Construction of a customer review visualization tool for MMA insurance. The system is comprised of a text pre-processing pipeline and a word cloud to display most prominent topics.
• Usability study, 2017
  • Usability engineering study at the usability laboratory of HAW Hamburg for Novomind AG.