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.

Publication

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]

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] [Presentation] [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] [Presentation] [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] [Presentation] [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.

2020

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.

2018

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.

Teaching

(short term) prediction methods - M1 Students - at ISTIC, Rennes 1 University. 2020-2023

For three years, I teached 30 hours of directed and practical work of prediction methods of time series. Throughout this teaching, I introduce prediction methods for time series such as exponential smoothing and auto regressive models. The end of the year is completed by a kaggle project I introduced on prediction of house prices.

Introduction to Machine Learning and Pandas - M1 Students - at Institut Agro Rennes. 2023

I teached 15h of directed and practical work introducing the classic machine learning approaches in Python. I presented the scikit-learn, numpy, and pandas libraries to allow students to conduct a machine learning project.

Introduction to Neural Network - M2 Students - at ENSAI. 2021-2022

I teached 20h of directed and practical work of introduction to neural networks. We introduce to students basic neural networks for tabular and image data on respectively wine and Cifar10 datasets. The final project was to implement a neural network to classify cats from dogs.

Oral Presentation for Technology Monitoring - M2 Students - at ISTIC, Rennes 1 University. 2020-2022

Evaluation of a report and an oral presentation of a scientific topic to be further investigated and reported. The purpose is to challenge the student to embrace scientific information and technology as well as to learn how to synthesise this information and present it in English.

Office tools for the statistician - L3 Students - at ENSAI. 2020-2022

For two years, I teached 20h of directed and practical work of office tools for the statistician such as Excel and Latex for two groups of first year student at ENSAI (École nationale de la statistique et de l'analyse de l'information). This first teaching experience was a good introduction for the exercise. Moreover, it was my only classroom teaching of the year due to the pandemic situation.

Object programming in Java - L2 Students - at ISTIC, Rennes 1 University. 2020-2022

For two years, I teached 20h of practical work in object programming in Java. The purpose of this course is to discover the concept of object programming, notion of inheritance and collections such as trees and lists. Throughout this teaching I learnt to teach distance learning course and interact with students through Microsoft Teams. I implemented the final project which consisted in creating a kind of tower defense video game.

Julien DELAUNAY

3rd year PhD student in Computer Science

INRIA Laboratory, LACODAM team

About Me

Publication

Work experience

2020 -

2022 - 2023

2020

2018

Education

Technical skills

Languages

Supervision

Organisation member

Julien DELAUNAY

3rd year PhD student in Computer Science

INRIA Laboratory, LACODAM team

About Me

Latest news

Publication

Work experience

2020 -

2022 - 2023

2020

2018

Teaching

Education

Technical skills

Languages

Supervision

Organisation member