I am a PhD candidate at the University of Toronto, supervised by Dimitrios Hatzinakos.
I am also a Postgraduate affiliate to the Vector Institute .
I am also the recipient of the DiDi scholarship for Biometrics research. My research interests are at the intersection
of signal processing and machine learning implemented in application for health care and biometrics.
I am broadly interested in deep learning, generative models and computer vision.
I graduated with a B.Sc./M.Sc, both in Electrical and Computer Engineering.
Before that, I have worked as a research fellow in the Visual Signal Analysis and Processing Center, KU, and Robotics Institute, KU and as an intern at
ICUBE Laboratory at the University of Strasbourg.
Selected Papers
PBGAN: Learning PPG Representations From GAN for Time-Stable and Unique Verification System
Dae Yon Hwang, Bilal Taha, Dimitrios Hatzinakos
IEEE Transactions on Information Forensics and Security 2021.
Evaluation of the time stability and uniqueness in PPG-based biometric system
Dae Yon Hwang, Bilal Taha, Da Saem Lee, Dimitrios Hatzinakos
IEEE Transactions on Information Forensics and Security 2020.
Learned 3D Shape Representations Using Fused Geometrically Augmented Images: Application to Facial Expression and Action Unit Detection
Bilal Taha, Munawar Hayat, Stefano Berretti, Dimitrios Hatzinakos, Naoufel Werghi
IEEE Transactions on Circuits and Systems for Video Technology 2020.
Teaching
Winter 2020, Fall (2020, 2021). ECE 1513: Teaching Assistant for Introduction to Machine Learning.
Fall (2019, 2020, 2021). ECE 302: Teaching Assistant for Probability and Applications.
Previous Teaching Experience: Introduction to computer Programming, Signals and Systems, Electromechanical Systems, University Physics 2.