Ahmed Mohamed Hussain

Research Interests

My research interests span a range of topics in computer security and privacy. Specifically, Large Language Models (LLMs) and Generative AI–specifically LLM security and trustworthiness, adversarial AI (such as jailbreaking and safety filter evasion), models fingerprinting, and parameter-efficient fine-tuning or domain adaptation for specialized tasks. Additionally, my interests include IoT security and privacy, edge AI, wireless network security (e.g., physical-layer authentication and radio-frequency fingerprinting), and privacy-preserving protocols.

Research Activities

My research combines theoretical analysis with practical implementations across computer security and privacy. In generative AI, my work covers evaluating LLM security through adversarial prompt processing and benchmarking, and exploring resource-efficient fine-tuning techniques for specializing LLMs in telecom automation and cybersecurity. Beyond LLMs, my research includes designing privacy-preserving protocols for wireless networks, leveraging edge AI for physical layer security and jammer localization, and securing vehicular and cyber-physical systems.

Collaborators

I collaborate with researchers from KTH, Uppsala University, Aalto University, Hamad Bin Khalifa University, and other institutions worldwide. My research benefits from working with experts in wireless security, machine learning, and systems security.

Please feel free to reach out if you would like to collaborate or do a BSc/MSc thesis with me. The vast majority of the thesis projects I supervise leads to a scientific publication(s).