Bevilacqua, F., Françoise, F., Fdili Alaoui, S., and Caramiaux B. (in press). Machine Learning in Movement-based Interaction for Performing Arts Applications.


Jourdan, T., Caramiaux, B. (2023). Culture and Politics of Machine Learning in NIME: A Preliminary Qualitative Inquiry. NIME 2023. PDF

Jourdan, T., Caramiaux, B. (2023). Machine Learning for Musical Expression: A Systematic Literature Review. NIME 2023. PDF

Sungeelee, V., Loriette, A., Sigaud, O., Caramiaux, B. (2023). Co-Apprentissage Humain-Machine: Cas d’Étude en Acquisition de Compétences Motrices. IHM’2023. PDF

Loriette, A., Liu, W., Bevilacqua, F., & Caramiaux, B. (2023). Describing movement learning using metric learning. PLoS One, 18(2), e0272509. PDF


Caramiaux, B., Fdili Alaoui, S. (2022). “Explorers of Unknown Planets”: Practices and Politics of Artificial Intelligence in Visual Arts. Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 477 (November 2022), 24 pages.

Sanchez, T., Caramiaux, B., Thiel, P., Mackay, W. (2022). Deep Learning Uncertainty in Machine Teaching. 27th Annual Conference on Intelligent User Interfaces (IUI) PDF
🏆 Best Paper Award


Vereschak, O., Bailly, G., Caramiaux, B. (2021). How to Evaluate Trust in AI-Assisted Decision Making? A Survey of Empirical Methodologies. In CSCW.
🏆 Best Paper Honorable Mention


Caramiaux, B., Françoise, J., Liu, W., Sanchez, T., & Bevilacqua, F. (2020). Machine Learning Approaches For Motor Learning: A Short Review. Frontiers in Computer Science, 2, 16.