Conferences#
- 📄 DISPERSE: Combating Congestion with Ensemble Job Recommendation by Camille Pliquet, Solal Nathan, Yann De Coster,
Bruno Crepon, 
Christophe Gaillac, 
Philippe Caillou, Michèle Sebag, RecSys, RecSys in HR, (
Code) 2026. - 📄 JoLA: Job Landscape Aware Job Recommendation by Solal Nathan, Guillaume Bied, Elia Perennes, Philippe Caillou, Bruno Crepon, Christophe Gaillac, Michèle Sebag, RecSys, RecSys in HR, (📄 Slides,
Code) 2025. - 📄 Fairness in job recommendations: estimating, explaining, and reducing gender gaps by Guillaume Bied, Christophe Gaillac, Morgane Hoffmann, Philippe Caillou, Bruno Crepon, Solal Nathan and Michèle Sebag, ECAI, AEQUITAS Workshop (📄 Slides), 2023.
- 📄 Toward Job Recommendation for All, by Guillaume Bied, Solal Nathan, Elia Perennes, Morgane Hoffmann, Philippe Caillou, Bruno Crepon, Christophe Gaillac and Michèle Sebag, IJCAI (AI And Social Good Track) (📄 Poster, 📄 Slides, Code), 2023. Also presented at ECML PKDD, AI4HR Workshop, 2023, and at JDSE [Best Talk Award], 2024.
- 📄 RECTO : REcommandation diminuant la Congestion par Transport Optimal, by Guillaume Bied, Elia Perennes, Solal Nathan, Victor Alfonso Naya, Philippe Caillou, Bruno Crepon, Christophe Gaillac and Michèle Sebag, APIA [Best Paper Award], 2023.
- 📄 Recommender system in a non-stationary context: recommending job ads in
pandemic times, by Guillaume Bied, Solal Nathan, Elia Perennes, Victor
Alfonso Naya, Philippe Caillou, Bruno
Crepon, Christophe
Gaillac and Michèle
Sebag, ECML PKDD, FEAST Workshop (📄 Poster), 2022.
- 📄 On the impact of overfitting in learning to rank using a margin loss: a case
study in job recommender systems by Solal Nathan and
Guillaume Bied, poster presented at
Baylearn and 
JDSE the same year (📄 Poster), 2022.
Internship reports#
Introduction à l’Apprentissage Automatique, Revue 3EI, 2022