Brief Bio

I am a Senior Researcher and a Senior Lecturer (Maitre Assistant) with the eXascale Infolab group (Department of Computer Science) and the Cognition and Perception Group (Department of Medicine) of the University of Fribourg, Switzerland. Previously, I was a postdoctoral researcher in the CMLA, a laboratory of Applied Mathematics at the Ens Paris Saclay. I received my Ph.D. (with highest honors) in Mathematics (Probability and Statistics) from the Ecole Normale Superieure Cachan / AMU, under the supervision of Pr. Etienne Pardoux.

My research interests include the development of theoretical and applied Machine Learning (ML) and Statistical Learning, with particular focus on Active Learning and applications to Healthcare problems and Neuroscience. Lead ML researcher in multiple projects, in collaboration with both international companies (Airbus, Thalès, Engie, Criteo …) and public institutions (hospitals, Public Healthcare administration, . . .).

Selected Healthcare Related Projects

• Smartcheck : Early detection of gait/postural control impairment in older adults Website | Selected Paper
• SmartRea : Monitoring Conciousness during Anesthesia Website | Selected Paper
• 5P : Detection of frailty in older adults Website | Selected Paper
• ZOOM : Faster, more accurate and more reliable method to quantify human perception Code | Selected Paper

2022/2023 Teaching

• Fall 2022:
  • Statistics (MSc)
• Spring 2023:
  • Formal Methods (BSc)
  • Introduction to human measures and their application (MSc)
  • Social Media Analytics - Recommender systems (MSc)

Selected 5 Publications (Google Scholar)

• Audiffren, J. (2021, July). Dichotomous optimistic search to quantify human perception. In International Conference on Machine Learning pdf
• Nicolaï, A., Limnios, M., Trouvé, A., & Audiffren, J. (2021). A langevin-based model with moving posturographic target to quantify postural control. IEEE Transactions on Neural Systems and Rehabilitation Engineering. pdf
• Audiffren, J., & Ralaivola, L. (2017). Bandits dueling on partially ordered sets. Advances in Neural Information Processing Systems. pdf
• Kadri, H., Duflos, E., Preux, P., Canu, S., Rakotomamonjy, A., & Audiffren, J. (2016). Operator-valued kernels for learning from functional response data. Journal of Machine Learning Research pdf
• Audiffren, J., & Ralaivola, L. (2015). Cornering stationary and restless mixing bandits with remix-ucb. Advances in Neural Information Processing Systems. pdf

PhD Student Supervision

PhD

I co-supervise(d) the following PhD students: Humbert, Pierre (2017-2021), Nicolai, Alice (2018-2021), and Laura Rettig (2017-Now).