About
Prof. Sonia Garcia is a faculty member at Telecom SudParis, holding the academic rank of Professor. Her primary research focuses on biometric analysis, medical signal processing, and machine learning applications in healthcare contexts. She has made significant contributions to understanding gait abnormalities in neurological disorders, handwriting analysis for early Alzheimer's detection, and enhancing security in biometric systems. Her work often integrates deep learning and statistical methods to analyze complex medical and behavioral data.
Prof. Garcia has authored over 50 peer-reviewed articles and holds multiple patents related to identity verification via handwritten signatures and gait analysis. Her research spans collaborations with medical institutions and tech firms to develop practical solutions for clinical diagnostics and security systems. Notable contributions include the development of the OSIRIS iris recognition software and methodologies for quantifying gait asymmetry using advanced mathematical models.
Her recent projects emphasize applying machine learning to predict treatment outcomes for neurological conditions and improving early detection of neurodegenerative diseases. This work has led to innovations in both algorithmic frameworks and biomedical engineering applications.
