Dr. Mohamed Shaban is a Tenured Associate Professor in the Electrical, and Computer Engineering department at the University of South Alabama (USA). He is also the director of the Computer Vision Laboratory at USA. He has previously served as an Assistant Professor of Computer Science at Southern Arkansas University, Graduate Teaching Assistant at the University of Louisiana at Lafayette and an Assistant Lecturer at Mansoura University.

Dr. Shaban has received the Ph.D., and M.S. degrees in Computer Engineering from the University of Louisiana at Lafayette in 2016, and 2012 respectively. He has also received the M.S. degree in Electrical Communications Engineering, and the B.S. degree (Excellent with Honors Degree) in Electronics, and Communications Engineering from Mansoura University, Egypt in 2010, and 2006 respectively. 

His current research interests are in the fields of Signal, and Image Processing for Biomedical Applications, Machine, and Deep Learning Applications, Edge Artificial Intelligence Optimization and Time-Series Analysis.

Mohamed Salama is a research assistant and a current member of the Computer Vision Laboratory. He is pursuing the Ph.D. in Systems Engineering (Electrical and Computer Engineering Track) at the University of South Alabama. He has received the M.S. and B.S. degrees in Communication and Computer Engineering from Benha University, Egypt in 2024 and 2020 respectively. He has previously served as an Assistant Lecturer at the College of Engineering, Benha University, Egypt. He is currently investigating and proposing novel machine and deep learning methods for the prediction of the onset of geomagnetic substorms. His assistantship is sponsored by NASA. 

Md. Ryhan Uddin is a research assistant and a current member of the Computer Vision Laboratory. He is pursuing the Ph.D. in Systems Engineering (Electrical and Computer Engineering Track) at the University of South Alabama. He has received the M.S. and B.S. degrees in Electronics and Telecommunication Engineering from Chittagong University of Engineering and Technology, Bangladesh in 2026 and 2024 respectively. He has previously served as a Lecturer at Bangladesh Army University of Engineering & Technology and as a Machine Learning Engineer. His research interests include computer vision, multimodal learning, signal and image processing, and edge AI. He is currently investigating novel deep learning methods for algal bloom detection and prediction. His assistantship is supported by EPA. 

Ralph Mouawad is a research assistant and a current member of the Computer Vision Laboratory. He is currently pursuing the B.S. in Mechanical Engineering at the University of South Alabama. He has received the B.S. in Computer Science from the University of South Alabama in 2026. His research interests include machine learning, data preprocessing, and artificial intelligence applications. He has also worked on software development, automation, and engineering projects. He is currently investigating the use of artificial intelligence to detect algae bloom and predict the related concentrations in creeks and rivers. His assistantship is sponsored by EPA.