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3rd year PhD student in Computer Science

INRIA Laboratory, LACODAM team

Work Experience Teaching Personnal Publication

About Me

I am 25 years old and currently in my third year of Ph.D. at Inria Rennes in France. I am a sociable, meticulous student with an excellent ability to multi-task and demonstrate great resistance to stress. I have skills in the fields of explainability, natural language processing, and human-computer interaction.

My thesis is about the Automatic Construction of Explanations for AI Models. My supervisors are Christine largouët and Luis Galárraga from the LACODAM team.

Due to recent advances in AI and in particular in deep learning, models are becoming more and more difficult to trust since their success is often due to their high complexity. Relying on the answers of a black box can be an issue for technical, ethical, and legal reasons. The purpose of my Ph.D. is to extend actual interpretable methods for machine learning methods to explain the inner mechanisms of a complex machine model.

Find my up-to-date CV here.


Julien Delaunay, Antoine Chaffin “Honey, Tell Me What's Wrong”, Global Explainability of NLP Models through Cooperative Generation Traitement Automatique du Langage Naturel (TALN 2023), Paris. [Full Text] [Presentation] [Code].

Julien Delaunay, Luis Galárraga, Christine largouët, Niels van Berkel Adaptation of AI Explanations to Users' Roles. Human-Centered Explainable AI (HCXAI 2023) CHI workshop, Hamburg. [Preprint] [Video].

Joel Wester, Julien Delaunay, Sander de Jong, Niels van Berkel On Moral Manifestations in Large Language Models. Moral Agents for Sustainable Transitions (CHI workshop 2023), Hamburg. [Preprint].

Julien Delaunay, Luis Galárraga, Christine largouët When Should We Use Linear Explanations? Conference on Information and Knowledge Management (CIKM 2022), Atlanta. [Full text] [Video] [Code].

Romaric Gaudel, Luis Galárraga, Julien Delaunay, Laurence Rozé, Vaishnavi Bhargava. s-LIME: Reconciling Locality and Fidelity in Linear Explanations. Intelligent Data Analysis (IDA 2022), Rennes. [Full text].

Julien Delaunay, Luis Galárraga, Christine largouët Improving Anchor-based Explanations. Conference on Information and Knowledge Management (CIKM 2020), Galway. [Preprint] [Video] [Code].

Luis Galárraga, Julien Delaunay, Jean-Louis Dessalles. REMI: Mining Intuitive Referring Expressions. International Conference on Extending Database Technology (EDBT/ICDT 2020), Copenhagen. [Technical report] [Full text] [Video] [Code].

Work experience

2020 -

  • PhD student supervised by Christine largouët and Luis Galárraga in the domain of interpretability
  • My Ph.D. focused on two tasks, firstly I studied the technical aspect of explanation, before moving on the human aspect. I hence studied when are linear explanations adapted to a model and target instance that leads to a publication in CIKM 2022. Following this, I visited the Human-Centred Computing group and conducted user studies to measure how feature-attribution, counterfactual, and rule-based explanation methods affect the users' trust and understanding.

    2022 - 2023

  • Visiting Researcher at Aalborg University in Danemark
  • In collaboration with Niels van Berkel, I conducted user studies to quantify the impact of three well-known explanation techniques (feature-attribution, rule-based, and counterfactual) on users' trust and understanding. This visit ended with the submission of a paper at VIS 2023.
    I have been lucky to meet a group of extremely talented and friendly colleagues there. Together we worked on two additional projects that lead to the publication of workshop papers at CHI 2023.


  • Internship supervised by Luis Galárraga and Christine largouët
  • I completed my research master's degree with a six months internship at Inria Rennes. This internship was part of the FABLE project (that leads to my PhD thesis.) I proposed a better discretization method to improve Anchors for tabular data and extended the latent research space used by Anchors to generate textual explanation. This internship ended with a publication in CIKM 2020.


  • Internship supervised by Luis Galárraga.
  • I completed my bachelor degree with a four months internship in a research laboratory. This was my first foot in the research, and I never leave it after. This internship in the domain of semantic web ended with the publication of an article concerning the mining of referring expressions in EDBT 2020. During this internship I coded a programm called REMI, supervised by Luis Galárraga.

    Rennes, France



    PhD student in computer science,
    University of Rennes 1, France, 2020-

    Research master's degree in computer science,
    University of Rennes 1, France, 2019-2020

    Master's degree in computer science,
    University of Sherbrooke, Canada, 2018-2019

    University degree MIAGE informatics methods applied to business management,
    University of Rennes 1, France, 2015-2018

    Scientific and european baccalaureate,
    High School St Martin, Rennes, France, 2012-2015

    Technical skills

  • Python
  • Java
  • Latex
  • Qualtrics
  • Prolifics
  • SQL
  • Html, css
  • Languages

    Native speaker
    Professional level
    Basic skills
    Beginner level


    Mentoring of Jacques Lacourt, a final year trainee at Centrale Marseille.

    Organisation member

  • 2020 - 2022
  • Member of the team organizing the monthly seminars of the Data Knowledge Management department at Inria/Irisa Rennes.
  • 2020 - 2022
  • Member of the Centre Committee at Inria Rennes where I represent the C College.
  • 2018
  • In charge of communication for the association of resident of Sherbrooke University. Agrus