Zahraa Tarek

About

Zahraa Tarek received a B.Sc. degree in Computer Science from the University of Mansoura, Egypt, in 2009 and a M.Sc. in Computer Science from Mansoura University in 2015. In 2015, she joined, as an assistant teacher, the Department of Computer Science, Mansoura University, and in 2017, she registered as a PhD research student in computer science department at the faculty of computer and information at the same university. She obtained the Ph.D. degree in Computer Science from the Faculty of Computers and Information in 2019. She has published many publications till now. Her research interests include Cloud Computing, Internet of Things, Fog Computing, Blockchain, Machine Learning, Software Engineering, Deep Learning, Regression models, Grid Search, Optimization Algorithms, Intelligent Systems, Smart Cities, Swarm Optimization, Genetic Algorithm, Fuzzy Theory, Classification, Supervised Learning, Scheduling, Load Balancing, Neural Networks and Artificial Intelligence, Pattern Recognition, Classification, Unsupervised Learning, Feature Extraction and Selection, Prediction, Machine Intelligence, Fuzzy Clustering, Predictive Modeling and Analytics, Medical Diagnosis, Face Recognition, Metaheuristic, Fuzzy Logic, Evolutionary Computation, Bio-Inspired Computing, Cybersecurity.

Employment

• Prince Sattam Bin Abdulaziz University Assistant Professor
  2024 - Present
• Mansoura University Faculty of Computers and Information Assistant Professor
  2020 - Present

Education

• Mansoura University Faculty of Computers and Information PHD
  2019 - Present
• Mansoura University Faculty of Computers and Information Master
  2011 - 2015

Projects & Funding

Projects & funding information is unavailable.

Publications (47)

• LiCPV: hybrid deep learning for PV fault detection
  Ain Shams Engineering Journal 2026 DOI: 10.1016/J.ASEJ.2026.104041
  +Save
• A novel dynamic horned lizard algorithm with advanced strategies for high-dimensional optimization and pathology lung cancer image segmentation
  Knowledge-Based Systems 2026 DOI: 10.1016/j.knosys.2026.115865
  +Save
• A Hybrid CNN–LSTM–GRU Deep Learning Model for the Accurate Classification of Chronic Kidney Disease
  Engineering, Technology & Applied Science Research 2025 DOI: 10.48084/etasr.14206
  +Save
• Credit Card Fraud Detection Based on a Hybrid CNN-RNN Deep Learning Model
  Engineering, Technology & Applied Science Research 2025 DOI: 10.48084/etasr.13938
  +Save
• Electricity Bill Prediction Based on a Particle Swarm Optimized Multilayer Perceptron Model
  Engineering, Technology & Applied Science Research 2025 DOI: 10.48084/etasr.14361
  +Save
• Enhancing Air Quality Index Classification Based on Ensemble Machine Learning Techniques
  Engineering, Technology & Applied Science Research 2025 DOI: 10.48084/etasr.13875
  +Save
• A Hybrid Deep Learning Framework Based on CNN-GRU-TabNet for the Predictive Modeling of COVID-19 Mortality
  Engineering, Technology & Applied Science Research 2025 DOI: 10.48084/etasr.13910
  +Save
• A novel RFE-GRU model for diabetes classification using PIMA Indian dataset
  Scientific Reports 2025 DOI: 10.1038/s41598-024-82420-9
  +Save
• A snake optimization algorithm-based feature selection framework for rapid detection of cardiovascular disease in its early stages
  Biomedical Signal Processing and Control 2025 DOI: 10.1016/j.bspc.2024.107417
  +Save
• Integrating Reconfigurable Intelligent Surface and Modified Aquila Optimization for Enhancing Wireless Communication Capacity
  IEEE Internet of Things Journal 2025 DOI: 10.1109/JIOT.2024.3508818
  +Save