Jill-Jênn Vie
Researcher at Inria, Lecturer at l’X & ENS
My research interests are AI applications to education. I train École polytechnique in competitive programming as ICPC coach, and I teach foundations of deep learning at ENS Paris.
- Our papers are being presented at UAI (Girard, Kallus, et al. 2026), ECML-PKDD (Girard, Minn, et al. 2026).
- Our papers were accepted at Journal of Computer-Assisted Learning (Kandemir et al. 2026), LAK (Kita et al. 2026), AIED (Nagai et al. 2026; Lbath et al. 2026), ICML workshop about graph foundation models (Zighem and Vie 2026).
We are hiring engineers, postdocs, or 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 about LLMs for learning programming.
Stay tuned for job offers, or contact me by mail1 (PGP
key).
Research Interests
- Knowledge tracing: learning a student model to predict student performance
-
Learning a student model on student data can be used to optimize teaching using model-based reinforcement learning or off-policy learning (Girard, Minn, et al. 2026).
More recently, I am interested in LLMs for learning programming, or thinkaloud data in problem solving.
Highest Peaks where I’ve been
See my projects and CV
- I developed the original adaptive test of Pix at the French Ministry of Education. This is free software that certifies the digital skills of all French citizens (Vie et al. 2017)
- We won a Google RISE Award for Prologin and founded the Girls Can Code! summer schools for K-12 girls, running since 2014
- Je suis membre du conseil scientifique de l’Éducation nationale, the scientific committee of the French MoE
Other former peaks: Pixar Animation Studios / The 2024 & 2025 ICPC World Finals / General Chair @ EDM 2021 / Yoko Kanno & THE SEATBELTS / Pass Culture / European Commission / Jury de l’agrégation d’informatique / Société informatique de France
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.” Proceedings of 9th Educational Data Mining in Computer
Science Education Workshop (CSEDM 2025) (Palermo, Italy),
July. https://hal.science/hal-05089333.
Choffin, Benoît, Fabrice Popineau, Yolaine Bourda, and Jill-Jênn Vie.
2019. “DAS3H: Modeling Student Learning and
Forgetting for Optimally Scheduling Distributed Practice of
Skills.” Proceedings of the
Twelfth International Conference on Educational Data Mining (EDM
2019), 29–38. https://arxiv.org/abs/1905.06873.
Girard, Samuel, Nathan Kallus, Jill-Jênn Vie, Arthur Gretton, Aurélien
Bibaut, and Houssam Zenati. 2026. “Fast
Best-in-Class Regret for Contextual Bandits.” The 42nd Conference on Uncertainty in Artificial
Intelligence (UAI 2026) (Amsterdam, Netherlands), August. https://inria.hal.science/hal-05640537.
Girard, Samuel, Sein Minn, Amel Bouzeghoub, and Jill-Jênn Vie. 2026.
“Counterfactual Learning of New Adaptive
Instructional Policies using Logged Data.” ECML-PKDD 2026 - European Conference on Machine Learning
and Principles and Practice of Knowledge Discovery in
Databases (Naples, Italy), September. https://inria.hal.science/hal-05640345.
Kandemir, Erva Nihan, Jill-Jênn Vie, Adam Sanchez-Ayte, Olivier Palombi,
and Franck Ramus. 2026. “Investigating the Influence of Training
Difficulty on the Learning Outcomes of Medical Students.”
Journal of Computer Assisted Learning 42 (1): e70172.
https://doi.org/https://doi.org/10.1002/jcal.70172.
Kita, Naoyuki, Jill-Jênn Vie, Koh Takeuchi, and Hisashi Kashima. 2026.
“Robust Post-Hoc Score Allocation in Exams.” The 16th
International Learning Analytics & Knowledge Conference, Bergen,
Norway. https://dl.acm.org/doi/full/10.1145/3785022.3785027.
Lbath, Mounir, Alexandre Parésy, Abdelkayoum Kaddouri, Abdelrahman
Zighem, and Jill-Jênn Vie. 2026. “Live Knowledge Tracing:
Real-Time Adaptation Using Tabular Foundation Models.” The
27th International Conference on AI in Education, Seoul, South
Korea. https://arxiv.org/abs/2602.06542.
Nagai, Ryosuke, Kyohei Atarashi, Koh Takeuchi, Jill-Jênn Vie, and
Hisashi Kashima. 2026. “Estimating Learners’ Skill Acquisition
Without Temporal Information.” The 27th International
Conference on AI in Education, Seoul, South Korea. https://arxiv.org/abs/2606.20611.
Vie, Jill-Jênn, and Hisashi Kashima. 2019. “Knowledge Tracing Machines: Factorization Machines for
Knowledge Tracing.” 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.”
Proceedings of the Fourth (2017) ACM Conference on Learning @
Scale, 323–26. https://github.com/jilljenn/las2017-wip/.
Zighem, Abdelrahman, and Jill-Jênn Vie. 2026. “Reinforcement
Learning Foundation Models Should Already Be a Thing.” https://arxiv.org/abs/2606.18812.