During her visit, Oumaima will collaborate with the AIRI@UTCN research community under the supervision of Prof. Mircea Giurgiu, contributing to research activities connected to the Romanian Hub for Artificial Intelligence - HRIA project. Her work focuses on the detection of neurological diseases using artificial intelligence and signal processing, with particular attention to non-invasive approaches for medical diagnosis and decision support.
Oumaima Majdoubi is a PhD researcher in Electrical Engineering affiliated with ENSAM Rabat - École Nationale Supérieure d'Arts et Métiers/ National Higher School of Arts and Crafts and ENSIAS -École Nationale Supérieure d'Informatique et d'Analyse des Systèmes/ National Higher School of Computer Science and Systems Analysis, both part of Mohammed V University in Rabat. She is a member of the Electronic Systems, Sensors and Nanobiotechnology - E2SN research team at ENSAM Rabat, where she is supervised by Prof. Ahmed Hammouch.
I combine a strong engineering foundation with advanced research in machine learning, deep learning, and voice signal analysis applied to healthcare. My work focuses on developing non-invasive, AI-driven approaches for the detection and severity assessment of neurodegenerative diseases, particularly Parkinson's disease, through speech and biomedical signal processing. My research interests lie at the intersection of artificial intelligence, biomedical signal processing, and digital health, with a growing focus on trustworthy AI, explainable models for medical decision support, and next-generation diagnostic systems.
Through this research visit, AIRI@UTCN continues to strengthen its international research collaborations and to support interdisciplinary work at the interface of artificial intelligence, biomedical engineering, and healthcare innovation.
Visiting researcher: Oumaima Majdoubi
Visiting period: 3 months
Grant: Eugen Ionescu Research Grant
Host supervisor: Prof. Mircea Giurgiu
Research topic: Detection of neurological diseases based on artificial intelligence and signal processing
Keywords: Artificial Intelligence, Biomedical Signal Processing, Machine Learning, Deep Learning, Voice Analysis, Parkinson’s Disease Detection, Neurological Disorders, Digital Health, Trustworthy AI
