Laurent El-Shafey awarded the EPFL PhD degree for his work on "Scalable Probabilistic Models For Face and Speaker Recognition"
On May 2 2014, Laurent El-Shafey made the public defense of his PhD thesis entitled "Scalable Probabilistic Models For Face and Speaker Recognition". He received the EPFL PhD thesis diploma from his thesis co-Director Sébastien Marcel.
Dr. Laurent El-Shafey proposed a general and scalable probabilistic linear discriminant analysis (PLDA) method that he applied to face and speaker recognition for biometric applications. He investigated more particularly: (1) an exact and scalable formulation of probabilistic linear discriminant analysis (PLDA), (2) an unified framework for three session variability modeling techniques: Inter-Session Variability modeling (ISV), Joint Factor Analysis (JFA) and Total Variability modeling (TV), (3) an efficient implementation of the proposed unified framework, (4) the validation of the proposed framework on three tasks: face recognition, speaker recognition and gender recognition. Additionally, he developed and proposed to the research community a new open source software library for signal processing and machine learning, as well as a set of reproducible research papers.
To download his thesis, click on the following link: Scalable Probabilistic Models for Face and Speaker Recognition