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  • Theo Jourdan

  • Post-doctorant
  • Équipe: ACIDE
  • Email: jourdan@isir.upmc.fr
  • Site web: https://hci.isir.upmc.fr/people/theo-jourdan/
  • Bio: I am postdoc researcher under the supervision of Baptiste Caramiaux in the ACIDE team at the ISIR laboratory. My research interests are machine learning, interaction design and specifically using machine learning algorithms to support exploration in music making. I focus on the study of machine learning technology situated in human musical practices. My research adopts a critical perspective on this technology, as a way to include socio-cultural aspects of musical expression. I hold a PhD from Institut National Sciences Appliquées (INSA) Lyon, made with Carole Frindel and Antoine Boutet, on privacy machine learning for healthcare.


  • Théo Jourdan, Baptiste Caramiaux. Culture and Politics of Machine Learning in NIME: A Preliminary Qualitative Inquiry. New Interfaces for Musical Expression (NIME), May 2023, Mexico, Mexico. ⟨hal-04075438⟩
  • Théo Jourdan, Baptiste Caramiaux. Machine Learning for Musical Expression: A Systematic Literature Review. New Interfaces for Musical Expression (NIME), May 2023, Mexico, Mexico. ⟨hal-04075492⟩
  • Théo Jourdan. Privacy and transparency in learning systems for healthcare. Biotechnology. Université de Lyon, 2021. English. ⟨NNT : 2021LYSEI074⟩. ⟨tel-03624466⟩
  • Théo Jourdan, Antoine Boutet, Carole Frindel. Privacy Assessment of Federated Learning using Private Personalized Layers. MLSP 2021 - IEEE International Workshop on Machine Learning for Signal Processing, Oct 2021, Queensland, Australia. pp.1-5, ⟨10.1109/MLSP52302.2021.9596237⟩. ⟨hal-03354722⟩
  • Noëlie Debs, Sergio Peignier, Clément Douarre, Théo Jourdan, Christophe Rigotti, et al.. Apprendre l'apprentissage automatique : un retour d'expérience. CETSIS 2021 - Colloque de l'Enseignement des Technologies et des Sciences de l'Information et des Systèmes, Jun 2021, Valenciennes, France. pp.1-5. ⟨hal-03341954⟩
  • Antoine Boutet, Carole Frindel, Sébastien Gambs, Théo Jourdan, Rosin Claude Ngueveu. DYSAN: Dynamically sanitizing motion sensor data against sensitive inferences through adversarial networks. ACM ASIACCS 2021 - 16th ACM ASIA Conference on Computer and Communications Security, Jun 2021, Hong Kong (Virtuel), China. ⟨10.1145/3433210.3453095⟩. ⟨hal-02512640v3⟩
  • Théo Jourdan, Noëlie Debs, Carole Frindel. The Contribution of Machine Learning in the Validation of Commercial Wearable Sensors for Gait Monitoring in Patients: A Systematic Review. Sensors, 2021, 21 (14), pp.4808. ⟨10.3390/s1010000⟩. ⟨hal-04211739⟩
  • Théo Jourdan, Antoine Boutet, Amine Bahi, Carole Frindel. Privacy-Preserving IoT framework for activity recognition in personal healthcare monitoring. ACM Transactions on Computing for Healthcare, 2020, 2 (1), pp.1-22. ⟨10.1145/3416947⟩. ⟨hal-03045108⟩
  • Noëlie Debs, Théo Jourdan, Ali Moukadem, Antoine Boutet, Carole Frindel. Motion sensor data anonymization by time-frequency filtering. 28th European Signal Processing Conference (EUSIPCO 2020), Aug 2020, Amsterdam, Netherlands. ⟨hal-02888083⟩
  • Théo Jourdan, Antoine Boutet, Carole Frindel. Vers la protection de la vie privée dans les objets connectés pour la reconnaissance d'activité en santé. Revue des Sciences et Technologies de l'Information - Série TSI : Technique et Science Informatiques, A paraître, pp.1-27. ⟨10.3166/RIA.28.1-27⟩. ⟨hal-02421854⟩
  • Théo Jourdan, Antoine Boutet, Carole Frindel. Toward privacy in IoT mobile devices for activity recognition. Privacy Preserving Machine Learning NeurIPS 2018 Workshop, Dec 2018, Montréal, Canada. pp.1-6. ⟨hal-01941453⟩
  • Théo Jourdan, Antoine Boutet, Carole Frindel. Toward privacy in IoT mobile devices for activity recognition. MobiQuitous 2018 - 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Nov 2018, New York city, United States. pp.1-10. ⟨hal-01882330⟩