معرفی
Rahul Yumlembam is a Research Fellow at Northumbria University's Computer and Information Sciences Department. His research focuses on AI-driven cybersecurity solutions, including ransomware detection, adversarial machine learning, and graph neural networks. He completed his PhD in 2024 with a thesis titled Enhancing Malware Mitigation using Graph Neural Networks, Adversarial Retraining and Conformal Prediction, supervised by Dr. B. Issac and Dr. L. Yang.
His work emphasizes explainable AI models and uncertainty quantification, with applications in IoT security, mobile malware analysis, and EEG-based robotics control. Recent publications address botnet detection, adversarial attack mitigation, and conformal prediction frameworks.
No scientific awards are listed. His academic contributions include interdisciplinary research at the intersection of cybersecurity and biomedical engineering.
