Dr. El Sayed Mahmoud
Professor and Program Coordinator of Computer Science at Sheridan
El Sayed's Scholarship Statistics: Research Projects: 17, HQP: 51, Publications: 22, Theses: 8
El Sayed's primary research interests are in the area of machine learning. The robustness and scalability of machine learning algorithms are limited by the amount of data available and the performance measures used to select the best model (or a combination of models) built. El Sayed aims to alleviate these limitations by investigating analytic models for machine-learning methods. This will allow computer scientist to derive theoretical guidelines to promote these methods' robustness while reducing their computational cost. El Sayed has derived a novel analytic model for a multiple classifier methodology that models the classification problem. This model breaks down the fitness of this methodology into three measurable components. The three components are measured during the construction of the multi-classifier based system to optimize its fitness and the computational cost.