Jill-Jênn Vie @jjvie

ML Researcher in RIKEN AIP & Kyoto Univ.

Our papers have been accepted to International Journal of Artificial Intelligence in Education (IJAIED, 2018) and STICEF!

I’m a researcher at RIKEN AIP (Tokyo) in the Human Computation team led by Hisashi Kashima, quite happy to live in Japan.
Feel free to say hi! I’m interested in everything. → vie@jill-jenn.net

My résumé / French version

Research Interests

Interactive Machine Learning

Adaptive algorithms, online matrix factorization, interactive recommender systems (if you like anime, try Mangaki)

Learning Analytics

How to use the logs of educational platforms (MOOCs, PIX) to improve learning?

Psychometrics

Multidimensional item response theory, cognitive diagnosis [slides], multistage testing [slides] [code]

Slides and benchmark code of my IACAT 2017 presentation in Niigata: Multistage Testing using Determinantal Point Processes
Slides and benchmark code of my IACAT 2017 presentation in Niigata: Multistage Testing using Determinantal Point Processes
Our publication Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario [arXiv] [slides] has been accepted to MANPU 2017 in Kyoto.
Our publication Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario [arXiv] [slides] has been accepted to MANPU 2017 in Kyoto.
I write free software for the French MoE: PIX is a certification of digital skills. Presented at Learning at Scale 2017 in Boston: [poster] [article]
I write free software for the French MoE:
PIX is a certification of digital skills.
Presented at Learning at Scale 2017 in Boston: [poster] [article]

Music

I enjoy playing Kapustin music and transcribing anime sheet music, see my YouTube videos.
I enjoy playing Kapustin music and transcribing anime sheet music, see my YouTube videos.
I composed the music of the TV show Blame the Algorithm using a Markov chain.
I composed the music of the TV show Blame the Algorithm using a Markov chain.

Achievements

2 books about algorithms & data structures
1 Python package: pip install tryalgo128 algorithms for coding contests
✅ A programming summer school for K-12 girlsGirls Can Code! since 2014
✅ An open-source anime recommender systemMangaki
✅ A TV show about algorithms that take control of our lives → Blame the Algorithm
✅ A data challenge with Kyoto University. [problem] [solutions]

❎ Play more Kapustin (so far only Etude 1)
❎ Write a screenplay for Ubik
❎ Read Yasutaka Tsutsui’s Gaspard in the Morning

Publications

See my Scholar page

Books

I co-wrote two books about algorithms and data structures: preparing programming contests and coding interviews (Dürr and Vie 2016) and (Belghiti, Mansuy, and Vie 2016).
The book is in French but the code is in Python: all 128 algorithms are on GitHub, in the Python package tryalgo.

Book Chapters

I wrote a chapter about adaptive assessment (Vie, Popineau, Bourda, et al. 2017) in a learning analytics book, where I identify similarities between cognitive diagnostic models and item response theory.

Conference Proceedings

I used to do cryptography in my master’s degree and published an article about leakage resilience (Abdalla and Vie 2012).
Used a General Diagnostic Model for adaptive testing and showed that it outperformed the DINA and Rasch models at predicting examinee performance (Vie et al. 2016).


Abdalla, Michel, and Jill-Jênn Vie. 2012. “Leakage-Resilient Spatial Encryption.” In International Conference on Cryptology and Information Security in Latin America, 78–99. Springer.

Belghiti, Ismael, Roger Mansuy, and Jill-Jênn Vie. 2016. Les clés pour l’info : ENS et Agrégation (option D). Calvage et Mounet.

Dürr, Christoph, and Jill-Jênn Vie. 2016. Programmation efficace. Ellipses.

Vie, Jill-Jênn, Fabrice Popineau, Yolaine Bourda, and Éric Bruillard. 2016. “Adaptive Testing Using a General Diagnostic Model.” In European Conference on Technology Enhanced Learning, 331–39. Springer.

———. 2017. “A Review of Recent Advances in Adaptive Assessment.” In Learning Analytics: Fundaments, Applications, and Trends, 113–42. Springer.

———. 2018. “Automated Test Assembly Using Determinantal Point Processes for Handling Learner Cold-Start in Large-Scale Assessments.” IJAIED: Learning at Scale: What Works & Lessons Learned, to appear.

Vie, Jill-Jênn, Fabrice Popineau, Éric Bruillard, and Yolaine Bourda. 2018. “Utilisation de tests adaptatifs dans les MOOC dans un cadre de crowdsourcing.” STICEF, to appear.

Vie, Jill-Jênn, Fabrice Popineau, Jean-Bastien Grill, Éric Bruillard, and Yolaine Bourda. 2015a. “Predicting Performance over Dichotomous Questions: Comparing Models for Large-Scale Adaptive Testing.” In 8th International Conference on Educational Data Mining.

———. 2015b. “Prédiction de performance sur des questions dichotomiques : comparaison de modèles pour des tests adaptatifs à grande échelle.” In Atelier Évaluation des Apprentissages et Environnements Informatiques.

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/blob/master/poster-las2017.pdf.

Vie, Jill-Jênn, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, and Hisashi Kashima. 2017. “Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario.” In Second International Workshop on Comics Analysis, Processing and Understanding. https://arxiv.org/abs/1709.01584.