Researcher in the fields of brain-computer interface (BCI), bio-signal processing, and machine learning. Ph.D. accomplishments include developing IMViS, a patented monitor for BCI applications, as well as a Spare-AutoEncoder (SAE)-based deep neural network for high-frequency visual evoked potential (VEP) classification. Hamid’s work in improving functionality of BCI has been recognized with scholarships and awards from Mitacs and Dal Innovates. Currently, Hamid is collaborating with the eye clinic of IWK hospital to apply machine learning methods for processing Sweep VEP signals to detect neurological diseases. Member of several professional societies such as IEEE/EMB and NeuroTechX.