I am interested in designing novel Data Visualizations tailored to mitigate the bias buried in Deep Neural Networks (DNNs) decisions to improve their Interpretability (XAI). I'm also working on building systems for the Authoring and Reverse-engineering of non-conventional visualizations drawn on paper. I defended my Ph.D. in 2022 at LIRIS lab, INSA-Lyon (France)! You can have more information about it here!
ECL MOS 5.5 - Interactive Data Visualization (Master level)
Visualization of Deep Neural Networks Lecture (1h30) at Ecole Centrale Lyon (ECL)
IA6 - HCI and AI (Master level)
Interpretability of Deep Learning Lecture (2 hours) at Lyon 1 University
IA5 - Bio-Inspired Intelligence (Master level)
Group Projects of Deep Q Networks (6 hours) at Lyon 1 University
ECL MOS 5.5 - Interactive Data Visualization (Master level)
Visualization of Deep Neural Networks Lecture (1h30) & Application Project (2 hours)
Group Projects of Visualizations (14 hours) Ecole Centrale Lyon (ECL)
IA6 - HCI and AI (Master level)
Interpretability of Deep Learning Lecture (2 hours) & Application project (2 hours) at Lyon 1 University
IA5 - Bio-Inspired Intelligence (Master level)
Group Projects of Deep Q Networks (6 hours) at Lyon 1 University
ECL MOS 5.5 - Interactive Data Visualization (Master level)
Group Projects of Visualizations (14 hours) at Ecole Centrale Lyon (ECL)
INF TC - Python (Undergraduate level)
Introduction to Python classes (8 hours) at Ecole Centrale Lyon (ECL)
DS2 - Data Visualization (Master level)
Group Projects of Visualizations (16 hours) at Lyon 1 University