Dr. Ammar Abasi holds a Ph.D. in Artificial Intelligence and Software Engineering from University Sains Malaysia and is an accomplished researcher with a strong academic and industry background. His expertise lies in AI security, machine learning, federated learning, and metaheuristic optimization, with a particular focus on securing 6G mmWave communications using advanced AI-driven techniques such as differential privacy and adversarial defense. He previously served as a postdoctoral fellow at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), where he led projects on secure federated learning and AI-based privacy frameworks. Dr. Abasi has authored over 60 peer-reviewed publications, received multiple IEEE Best Paper Awards (including at GLOBECOM 2022 and MeditCom 2022), and is an active member of professional organizations such as IEEE, ComSoc, and IEEE Young Professionals. He regularly contributes to international conferences, furthering research in AI, machine learning, and cybersecurity.