PhD (Electrical Engineering), FAST NUCES, 2024

MS (Electrical Engineering), NUST, 2019

BS (Electrical Engineering), AIR University, 2014

Dr. Irum Saba is an assistant professor at the National University of Computer and Emerging Sciences (NUCES-FAST). She has a strong academic and research background in machine learning (ML), reinforcement learning (RL), and deep reinforcement learning (DRL), with a keen interest in applying these advanced techniques to address complex, real-world problems. Her current research focuses on the security of digital twins in vehicle-to-grid (V2G) networks, and she is also eager to explore other innovative ML, RL, and DRL applications across diverse domains.
Dr. Saba has contributed to several high-impact publications in leading international journals. Her recent work includes studies on optimizing electric vehicle energy management using digital twins and TD3 algorithms, multi-agent reinforcement learning for dynamic resource optimization in V2G networks, and deep reinforcement learning approaches for electric vehicle battery state-of-charge estimation. She has also co-authored research addressing threats, vulnerabilities, and mitigation strategies in V2G networks. Some of her notable publications appear in journals such as the IEEE Transactions on Intelligent Transportation Systems, IET Smart Grid, and Springer Nature.
Dr. Saba’s broader research interests include network resource management, smart grid optimization, intelligent transportation systems, and cybersecurity for digital twins. She is passionate about exploring intelligent algorithms to improve system performance, enhance security, and support efficient decision-making in emerging technologies.