Dr. Rami Mustafa A. Mohammad
Distinguished Cybersecurity Research Leader & AI Innovation Pioneer
Leading groundbreaking research at the intersection of artificial intelligence and cybersecurity, pioneering innovative solutions that shape the future of digital security and intelligent systems. Recognized globally for exceptional contributions to machine learning, intrusion detection, and IoT security frameworks.
About Dr. Rami Mustafa
A distinguished academic leader revolutionizing cybersecurity through artificial intelligence
Academic Excellence & Leadership
Dr. Rami Mustafa A. Mohammad stands as a beacon of innovation in the rapidly evolving landscape of cybersecurity and artificial intelligence. His extraordinary journey as a researcher and academic leader has positioned him among the Top 2% of researchers worldwide, a testament to his groundbreaking contributions to the field.
Research Philosophy & Impact
With an unwavering commitment to advancing the frontiers of knowledge, Dr. Mohammad has dedicated his career to bridging the gap between theoretical innovation and practical application. His research philosophy centers on developing intelligent solutions that not only push the boundaries of academic understanding but also address real-world cybersecurity challenges faced by organizations globally.
Global Recognition & Influence
Currently serving at the prestigious SAUDI ARAMCO Cybersecurity Chair at Imam Abdulrahman Bin Faisal University, Dr. Mohammad has established himself as a thought leader whose work influences policy, industry standards, and academic curricula worldwide. His research spans across multiple disciplines, creating synergies between cybersecurity, machine learning, and digital forensics.
Core Expertise
Pioneering research across multiple domains of cybersecurity and artificial intelligence
Advanced Cybersecurity
Developing next-generation security frameworks, intrusion detection systems, and threat analysis methodologies that protect critical infrastructure and digital assets.
Artificial Intelligence & ML
Creating intelligent algorithms and machine learning models that revolutionize cybersecurity, featuring selection optimization, and pattern recognition.
IoT Security Frameworks
Designing comprehensive security architectures for Internet of Things ecosystems, addressing vulnerabilities in connected devices and networks.
Digital Forensics
Advancing digital investigation techniques, evidence analysis methodologies, and forensic tools for wearable devices and emerging technologies.
Cloud Computing Security
Optimizing cloud-based security solutions, task scheduling algorithms, and performance analysis for distributed computing environments.
Optimization Algorithms
Developing bio-inspired optimization techniques, whale optimization algorithms, and feature selection methodologies for enhanced system performance.
Latest Research Publications
Cutting-edge research that's shaping the future of cybersecurity and AI
WristSense Framework: Forensic Analysis of Wearable Devices
Forensic Science International: Digital Investigation, 2025
Revolutionary framework for exploring forensic potential of wrist-wear devices through comprehensive case studies, introducing novel approaches to digital evidence analysis in wearable technology.
Download Full PaperAdvanced Click Fraud Detection Using Machine Learning and Deep Learning
IEEE Access, 2025
Comprehensive study employing sophisticated ML and DL algorithms for ad click fraud detection, featuring innovative feature engineering and extraction approaches.
Download Full PaperKashif: Arabic Content Classification Chrome Extension
Applied Sciences, 2024
Innovative machine learning-based Chrome extension for intelligent classification of Arabic content on web pages, addressing unique challenges in multilingual cybersecurity.
Download Full PaperIntrusion Detection Using Improved Cuckoo Search Optimization
Journal of Wireless Mobile Networks, 2024
Enhanced intrusion detection system utilizing improved Cuckoo Search optimization algorithm for intelligent cybersecurity models with superior feature selection capabilities.
Download Full PaperClick Fraud Detection for Online Advertising
Egyptian Informatics Journal, 2023
Machine learning-based approaches for detecting fraudulent clicks in pay-per-click advertising systems, protecting advertiser investments and maintaining digital advertising integrity.
Download Full PaperVoting-Based Deep CNNs for Signal Classification
Electronics, 2023
Novel voting-based deep convolutional neural networks for M-QAM and M-PSK signals classification, achieving superior performance in automatic modulation classification.
Download Full PaperIoT Intrusion Detection with Feature Extraction
Journal of Sensor and Actuator Networks, 2023
Advanced intrusion detection system using sophisticated feature extraction techniques with machine learning algorithms specifically designed for IoT environments.
Download Full PaperIoT Unauthorized Access Detection Using Machine Learning
Journal of Sensor and Actuator Networks, 2023
Comprehensive machine learning-based detection system for unauthorized access to IoT devices, addressing critical security vulnerabilities in connected device ecosystems.
Download Full PaperImproved Whale Optimization with Local-Search for Feature Selection
Computers, Materials & Continua, 2023
Innovative hybrid approach combining Whale Optimization Algorithm with Great Deluge local search method for enhanced feature selection in machine learning applications.
Download Full PaperCloud Computing Task Scheduling Using CloudSim
Mathematical Modelling of Engineering Problems, 2022
Comprehensive modeling and analysis of task scheduling algorithms in cloud computing environments, comparing performance metrics using advanced CloudSim simulation techniques.
Download Full PaperMachine Learning Models Towards Prediction of COVID and Non-COVID 19 Patients in the Hospital’s Intensive Care Units (ICU)
Mathematical Modelling of Engineering Problems, 2022
Towards Prediction of COVID and Non-COVID 19 Patients in the Hospital’s Intensive Care Units (ICU)
Download Full PaperResearch Collaboration & Contact
Open to innovative research partnerships and academic collaborations worldwide
Research Collaborations
I actively seek partnerships with researchers, institutions, and industry leaders to advance cybersecurity and AI research.
Full Article Requests
Request complete research papers, technical reports, and detailed methodologies from my publication portfolio.
Academic Mentoring
Available for PhD supervision, research guidance, and academic consultation in cybersecurity and AI domains.
Direct Contact
Email: rmmohammad@iau.edu.sa
Institution: Imam Abdulrahman Bin Faisal University
Position: SAUDI ARAMCO Cybersecurity Chair