Sherif E. Abdelhamid

Also published under:Sherif Abdelhamid, Sherif Elmeligy Abdelhamid

Affiliation

Computer & Information Sciences, Virginia Military Institute, Lexington, VA, USA

Topic

Convolutional Neural Network,Machine Learning,Support Vector Machine,Deep Learning,Ensemble Method,F1 Score,Grayscale Images,Artificial Neural Network,Binary Classification,Classification Accuracy,Convolutional Layers,Decision Tree,Deep Learning Models,Ensemble Model,Gamification,Generative Adversarial Networks,Internet Of Things,K-nearest Neighbor,Learning Environment,Learning Management System,Machine Learning Models,Random Forest,Student Engagement,US Government,Visual Geometry Group,Accuracy Of Model,Adaptive Learning,Adversarial Attacks,Artificial Intelligence Models,Auditory Channel,Automatic Detection,Average Accuracy,Average Peak Signal-to-noise Ratio,Base Learners,Bayesian Regression,Behavioral Characteristics,Binary Model,Class Balance,Classification Datasets,Classification Problem,Clear Sky,Color Images,Combined Feature Set,Combined Set,Computer Science,Conceptual Understanding,Constructivist Learning Theory,Contextual Cues,Cryptosystem,Cybercrime,

Biography

Sherif E. Abdelhamid received the B.Sc. and M.Sc. degrees in computer science from AAST, Alexandria Campus, Egypt, and the M.Sc. and Ph.D. degrees in computer science from Virginia Tech. He was also an Infrastructure Software Engineer with the Center for Open Science, Charlottesville, VA, USA. He is currently an Assistant Professor with the Department of Computer and Information Sciences, Virginia Military Institute (VMI). Before joining VMI, he was an Assistant Professor with the College of Computing and Information Technology (AAST-Smart Village Campus), Egypt. His research work spans three main fields, such as computer science, STEM education, and public health. His research interests include high-performance services-based computing solutions, novel digital educational technologies, and tools for the social network analysis of complex systems.