PhD Theses

Foteini  Agrafioti (University of Toronto), “ECG in Biometric Recognition: Time Dependency and Application Challenges”, Advisor: Dimitrios Hatzinakos (2011)

As biometric recognition becomes increasingly popular, the fear of circumvention, obfuscation and replay attacks is a rising concern. Traditional biometric modalities such as the face, the fingerprint or the iris are vulnerable to such attacks, which defeats the purpose of biometric recognition.

Je-Won Kang(University of Southern California), “Efficient coding techniques for high definition video”, Prof. C.-C. Jay Kuo, 2012

Yuehao Wu, (University of Delaware), “Compressive optical imaging systems”, Advisor: Prof. Dennis W. Prather, 2012.

Angshul Majumdar (University of British Columbia), “A Sparsity Based Approach Towards Fast MRI Acquisition”, Advisor: Prof. Rabab K. Ward, 2012

Magnetic Resonance Imaging (MRI) is a safe medical imaging modality that can acquire high quality scans. However, MRI has a relatively long acquisition time. Reducing the MRI data acquisition time had been a challenge to researchers for the last two decades. In this thesis, the author proposed Compressed Sensing based techniques to speed-up MRI scans.