TechFusion 2025 - AI, Cybersecurity, and Emerging Trends in Computer Science

Israa Sabry Fahmy

Biography

Israa Fahmy is a Generative AI PhD Candidate and Research Assistant at the 6G Research Center at Khalifa University, where she also teaches Data Science, and Artificial Intelligence as a lab instructor. Her current research explores the intersection of Generative AI and next-generation wireless systems, leveraging diffusion models and large language models to design intelligent, adaptive, and energy-efficient 6G networks.
Before pursuing her PhD, Israa earned her Bachelor' s degree in Computer Engineering and Mathematics from the American University in Cairo with Highest Honors, and her Master' s in Machine Learning from Khalifa University, graduating top of her class. She is also pursuing an MBA with One League, specializing in Statistics and Data Science, and has been recognized with the Top Performing Award from MIT' s Institute for Data, Systems, and Society.
Throughout her career, Israa has collaborated with leading organizations including Apple and GSMA, contributing to global AI initiatives and open benchmarks for telecom LLMs. Her work bridges research and real-world impact, driven by a strong commitment to ethical and responsible AI and to empowering the next generation of innovators.

Research Interest

Her work bridges research and real-world impact, driven by a strong commitment to ethical and responsible AI and to empowering the next generation of innovators.

Abstract

Generative Diffusion Models for Adaptive Optimization in 6G Networks: As 6G networks evolve toward hyper-connectivity, dynamic optimization of network behavior becomes a critical challenge. This presentation introduces a novel approach leveraging generative diffusion models and reinforcement learning to optimize handover and access procedures in dynamic wireless environments. By modeling complex solution distributions and integrating generative priors into policy learning, this framework enables more resilient and adaptive decision-making in scenarios involving mobility, interference, and radio link failures. The talk highlights how generative modeling can reshape the design of intelligent network control systems, paving the way toward self-optimizing, AI-driven 6G architectures