Jill-Jênn Vie

Researcher at Inria, Lecturer at l’X

I am a researcher at Inria, Soda team and a lecturer at École polytechnique and ENS Paris where I teach competitive programming (Polytechnique won ICPC SWERC 2024 🥇🏆) and deep learning. My research interests are recommender systems and application of machine learning and reinforcement learning to education (Vassoyan et al. 2024).

We are hiring engineers, postdocs and PhD students, as we were awarded an IA-Cluster chair about ATLAS: AI for teaching and learning at scale at Paris-Saclay University & an ANR JCJC grant that I can share with interested people. You can either wait for a more precise job offer description, or directly reach out with a CV.

Feel free to contact me by mail (PGP key).

Research Interests

Knowledge tracing: predicting student performance: Training a student model on student data can be used to optimize teaching using reinforcement learning.
I am also interested in synthetic tabular data generation (Vie*, Rigaux*, and Minn 2022).
Recommender systems: collaborative filtering: We study applications of collaborative filtering for education, personalized medicine (Réda, Vie, and Wolkenhauer 2025a, 2025b) and diversity of recommendations using determinantal point processes (pass Culture, Kyoto U) [slides] (Ibrahim et al. 2025).

Our article Knowledge Tracing Machines has been presented at AAAI 2019. See also our code & tutorial (Vie and Kashima 2019). — Our article **Knowledge Tracing Machines** has been presented at **AAAI 2019**. See also our code & tutorial (Vie and Kashima 2019).

We received the Best Paper Award at EDM 2019 for our learning/forgetting student model DAS3H (Choffin et al. 2019). — We received the **Best Paper Award** at **EDM 2019** for our learning/forgetting student model **DAS3H** (Choffin et al. 2019).

Highest Peaks where I’ve been

See my projects and CV

Government & State Startups

I developed the original adaptive test of Pix @ French Ministry of Education. This is free software that certifies the digital skills of all French citizens (Vie et al. 2017)
We optimized the diversity of recommendations to encourage discovery on French citizens with Pass Culture ~ French Ministry of Culture (Ibrahim et al. 2025)
European Commission
Jury de l’agrégation d’informatique ; avec Marc Jeanmougin nous avons fait l’environnement de concours NonOS
Jury du concours X, ENS
J’ai rejoint le conseil scientifique de l’Éducation nationale

Programming

Using a Google RISE Award, we founded the Girls Can Code! summer schools for K-12 girls running since 2014
The 2024 & 2025 ICPC World Finals with students from École polytechnique
Président de Prologin
Secrétaire de la Société informatique de France

Abroad

Mt Fuji, 3776 m
AAAI 2019, General Chair @ EDM 2021, NeurIPS 2024
Pixar Animation Studios
I’ve seen Yoko Kanno & THE SEATBELTS in concert

Collaborators

Tomas Rigaux, Hisashi Kashima and Koh Takeuchi from Kyoto University: associated team RED
Clémence Réda @ CNRS, IBENS
Franck Silvestre @ IRIT
Luc Rocher @ Synthetic Society Lab @ University of Oxford

Selected Publications

See all publications / My Scholar page

Agrawal, Anav, and Jill-Jênn Vie. 2025. “AlgoAce: Retrieval-Augmented Generation for Assistance in Competitive Programming.” In Proceedings of 9th Educational Data Mining in Computer Science Education Workshop (CSEDM 2025). Palermo, Italy. https://hal.science/hal-05089333.

Choffin, Benoı̂t, Fabrice Popineau, Yolaine Bourda, and Jill-Jênn Vie. 2019. “DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Skills.” In Proceedings of the Twelfth International Conference on Educational Data Mining (EDM 2019), 29–38. https://arxiv.org/abs/1905.06873.

Ibrahim, Carole, Hiba Bederina, Daniel Cuesta, Laurent Montier, Cyrille Delabre, and Jill-Jênn Vie. 2025. “Diversified recommendations of cultural activities with personalized determinantal point processes.” In Proceedings of RecSoGood workshop at RecSys 2025, in press. Prague, Czech Republic.

Réda, Clémence, Jill-Jênn Vie, and Olaf Wolkenhauer. 2025a. “Comprehensive evaluation of pure and hybrid collaborative filtering in drug repurposing.” Scientific Reports 15 (2711): 2711. https://doi.org/10.1038/s41598-025-85927-x.

———. 2025b. “Joint Embedding-Classifier Learning for Interpretable Collaborative Filtering.” BMC Bioinformatics 26 (1): 26. https://doi.org/10.1186/s12859-024-06026-8.

Vassoyan, Jean, Anan Schütt, Jill-Jênn Vie, Arun-Balajiee Lekshmi-Narayanan, Elisabeth André, and Nicolas Vayatis. 2024. “A Pre-Trained Graph-Based Model for Adaptive Sequencing of Educational Documents.” https://inria.hal.science/hal-04779162.

Vie, Jill-Jênn, and Hisashi Kashima. 2019. “Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing.” In Proceedings of the 33th AAAI Conference on Artificial Intelligence, 750–57. https://arxiv.org/abs/1811.03388.

Vie, Jill-Jênn, Fabrice Popineau, Françoise Tort, Benjamin Marteau, and Nathalie Denos. 2017. “A Heuristic Method for Large-Scale Cognitive-Diagnostic Computerized Adaptive Testing.” In Proceedings of the Fourth (2017) ACM Conference on Learning @ Scale, 323–26. ACM. https://github.com/jilljenn/las2017-wip/.

Vie*, Jill-Jênn, Tomas Rigaux*, and Sein Minn. 2022. “Privacy-Preserving Synthetic Educational Data Generation.” In Proceedings of EC-TEL 2022. Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption, 393–406. https://hal.archives-ouvertes.fr/hal-03715416.