Dr. Fabrice Vaussenat | Sleep Disorder | Best Scholar Award

Dr. Fabrice Vaussenat | Sleep Disorder | Best Scholar Award 

Dr. Fabrice Vaussenat, École de technologie supérieure, Canada

Dr. Fabrice Vaussenat is an accomplished researcher and educator specializing in biomedical engineering, artificial intelligence, and signal processing. Based in Montréal, Canada, Dr. Vaussenat currently serves as a Chercheur Institutionnel in Génie Électrique at the École de technologie supérieure (ETS). He earned his Diploma in Medicine and a Master’s non-Thesis in Electronics, Electrotechnics, and Automation from Université de Montpellier II, followed by a Doctorate in Biomedical Engineering from Université de Technologie de Compiègne. Dr. Vaussenat has been recognized for his academic and entrepreneurial achievements, notably winning the Prix du parcours le plus inspirant from COPL in 2023. His career includes significant roles such as CEO and Director of Research at Inomedis and Devinnova, where he led the development of innovative medical devices. His research focuses on physiological modeling, artificial organs, and the application of machine learning to biomedical signals. Dr. Vaussenat has also supervised several Master’s and Doctorate students, contributing to advancements in EEG, ECG signal acquisition, and deep learning for health monitoring. His work has been widely published, showcasing his contributions to both academia and industry.

Professional Profile:

ORCID

 

Summary of Suitability for Best Scholar Award

Dr. Fabrice Vaussenat is a highly qualified candidate for the Research for Best Scholar Award based on his extensive academic and professional background, as well as his significant contributions to the field of biomedical engineering and related disciplines.

Degrees:

  • 🎓 Diploma in Medicine: Université de Montpellier II (Languedoc)
  • 🎓 Master’s non-Thesis in Electronics, Electrotechnics, Automation: Université de Montpellier II (Languedoc)
  • 🎓 Doctorate in Biomedical: Université de Technologie de Compiègne

Recognitions:

  • 🏆 2023/6 Prix du parcours le plus inspirant: COPL
  • 📜 2021/4 Lettre de recommandation: Pr. Thibaut Desmettre, Pôle Urgences – SAMU – Réanimation Médicale
  • 🏅 2020/9 Produit ou service de l’année: Les Inn’Ovations
  • ❤️ 2019/9 Prix coup de cœur du challenge en cardiologie: e-HealthWorld Monaco
  • 🧒 2018/9 Prix de la Fondation Saint-Pierre: Fondation Saint Pierre

Research Specialization Keywords:

  • Biomedical
  • Artificial Organs
  • Physiological Modeling
  • Artificial Intelligence
  • Machine Learning
  • Signal Processing

Employment:

  • 📅 2022/7 – Present: Chercheur Institutionnel Génie Électrique, École de technologie supérieure
  • 🏥 2020/2 – 2023/8: Chercheur Associé, Cardiologie, Centre hospitalier de l’Université de Montréal
  • 💼 2017/8 – 2021/10: CEO – Directeur de Recherche – Fondateur, Inomedis
  • 📈 2014/2 – 2021/10: CEO – Directeur de Recherche – Fondateur, Devinnova
  • 💻 2006/2 – 2014/2: CEO – Directeur de Recherche – Fondateur, SyComCare
  • 🌍 1996/9 – 2006/2: Responsable Europe des sciences de la donnée médicale, Fresenius Medical Care

Student/Postdoctoral Supervision:

  • 🎓 Master’s Thesis (n=3)
    • 2022/9 – 2025/9: Alexandre Perroton (In Progress), ETS
    • 2022/9 – 2025/9: Emile Normand (In Progress), ETS
    • 2022/9 – 2023/6: Julie Payette (Completed), ETS
  • 🎓 Doctorate (n=4)
    • 2023/9 – 2027/9: Fatemeh Javadi (In Progress), ETS
    • 2023/6 – 2026/9: Julie Payette (In Progress), ETS
    • 2022/9 – 2025/9: Manisha Mahagammulle (In Progress), ETS
    • 2022/9 – 2026/9: Abhiroop Bhattacharya (In Progress), ETS

 

Publication top Notes:

Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms

Heart Rate Measurement Using the Built-In Triaxial Accelerometer from a Commercial Digital Writing Device

Continuous Critical Respiratory Parameter Measurements Using a Single Low-Cost Relative Humidity Sensor: Evaluation Study

Continuous Critical Respiratory Parameter Measurements Using a Single Low-Cost Relative Humidity Sensor: Evaluation Study (Preprint)