About me

Contact

• Solal Nathan
• You can contact me by mail firstname.lastname [at] {lisn,upsaclay,ens-paris-saclay,inria} [dot] fr
• On Mastodon

Schooling

• PhD Student at LISN in the A&O team, under the supervision of Michèle Sebag and Philippe Caillou in the Vadore project
• PhD title: Job Recommender Systems: An Optimal Transport Approach
• Student at Université Paris-Saclay in the M2 IA
• Normalien at ENS Paris-Saclay

Publications

Conferences

• 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, presented at ECML (Poster), 2022.
• On the impact of overfitting in learning to rank using a margin loss: a case study in job recommender systems by Guillaume Bied and Solal Nathan, poster presented at Baylearn and JDSE the same year (Poster), 2022.

Scientific mediation

• Introduction à l’Apprentissage Automatique, Revue 3EI, 2022
• Word Embedding Introduction, Revue 3EI, 2022

Internship reports

• M2 Internship: Combatting Unemployment: Data, Recommendations and Fairness, 2022.
• ARPE: 3D Reconstruction using Implicit Function Methods: PiFU, NeRF, Novel View Synthesis, Neural Rendering and more presented as a Poster, 2021.
• M1 Internship: Differential Privacy applied to Crowd Density Estimation, presented as a Poster, 2020.

Teaching and Mediation

• Advanced Optimization and Automated Machine Learning (M2), Lecturer on Unconstrained and Constrained Optimization, with Isabelle Guyon, Marc Schoenaer, Lisheng Sun-Hosaya, Haozhe Sun, Romain Egele, 2023.
• Introduction to Statistical Learning (L3), seminar supervisor, with François Landes
• Introduction aux Sciences des Données (L1), practical work supervisor, with Nicolas Thiery and Fanny Pouyet
• Inria Stand, Introduction to Algorithm and Cryptography, Fête de la Science, 2022.

CV

• My Curriculum Vitae