Mathematical Modeling, AI Security, and Trustworthy Cyber-Physical Systems

Dr. Marwan Omar is an Associate Professor of Cybersecurity and Artificial Intelligence at the Illinois Institute of Technology and an internationally recognized researcher in AI security, adversarial machine learning, secure software engineering, and intelligent systems. His research focuses on securing large language models (LLMs), autonomous AI agents, agentic AI ecosystems, adversarial attacks and defenses, AI governance, trustworthy AI, and secure machine learning systems for critical infrastructure. In addition to his academic career, Dr. Omar has extensive industry experience as a Chief AI Officer, AI Security Engineer, penetration tester, and cybersecurity consultant, leading AI security assessments, red teaming engagements, secure AI architecture reviews, and enterprise AI governance initiatives across public and private sectors. Dr. Omar has authored numerous peer-reviewed publications in cybersecurity and artificial intelligence and serves as editor of multiple books on AI security and autonomous intelligent systems. His research integrates mathematical modeling, machine learning, optimization, and cybersecurity to improve the robustness, resilience, and trustworthiness of intelligent systems deployed in high-risk environments. His current work emphasizes securing agentic AI platforms, defending against prompt injection and adversarial attacks, protecting retrieval-augmented generation (RAG) systems, AI governance frameworks, and mathematical approaches for evaluating AI robustness.