Dr. Rahama Salman
Jazan University, MESCO Institute of Management and Computer Sciences, SAM GLOBAL UNIVERSITY
0000-0003-4105-5019
About
Dr. Rahama Salman has been serving as an Assistant Professor in the Department of Computer Science at the College of Engineering & Computer Science, Jazan University, KSA, since 2012. Before joining Jazan University, she worked as a Lecturer at MIMCS, India.
She earned her Ph.D. in Computer Science from SAM Global University, MP, in 2024. She holds a Master’s degree in Computer Science Applications and a Bachelor’s degree in Mathematics, Statistics, and Computer Science from Osmania University, Hyderabad, India.
Her Ph.D. research focused on Machine Learning & Deep Learning, with a specialized interest in Artificial Intelligence and Networking. She has published numerous research papers in reputed journals, contributed to book chapters, and actively participated in international conferences covering diverse topics such as Deep Learning, IoT, and Edge Computing.
With 15 years of teaching experience, Dr. Salman’s research primarily revolves around:
Prediction of chronic diseases with enhanced accuracy and precision using hybrid Deep Learning and Machine Learning classifiers.
Network intrusion detection utilizing hybrid network techniques.
Deep-Q residue analysis in computer vision datasets using Support Vector Machines (SVMs).
Her contributions continue to advance research in AI, networking, and computational intelligence.
Employment
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Jazan University LECTURER2012 - Present
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MESCO Institute of Management and Computer Sciences Lecturer2009 - 2012
Education
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SAM GLOBAL UNIVERSITY Ph.D2020 - 2024
Projects & Funding
Projects & funding information is unavailable.
Publications (10)
- AI DRIVEN GAME THEORY OPTIMIZED GENERATIVE CNN-LSTMMETHOD FOR FAKE CURRENCY DETECTION Save
- Employing a Hybrid Convolutional Neural Network and Extreme Learning Machine for Precision Liver Disease Forecasting Save
- DeepQ classification automated disease classification in global perspective approach and predictive decision using tensor flow Save
- Classification and Prediction of Medical Dataset Using Ensemble DeepQ Classifier Save
- Customer Retention Using Machine Learning Save
- DeepQ Residue Analysis of Computer Vision Dataset using Support Vector Machine Save
- Efficient Chronical Disease Prediction Using Improved Convolutional Neural Network Model Save
- Networks Intrusion Detection Using Optimized Hybrid Network Save
- Novel Technique in Content Based Image Retrieval using Classification by Deep Learning in Artificial Intelligence Save
- ADAPTIVE DEEP LEARNING FRAMEWORK FOR ROBUS QR CODE WATERMARKING WITH NOISE-AWARE PRESERVATION Save