6 papers
Engineering Trustworthy Agentic AI for Critical Systems
Omar Al-Refai, Ibrahim Shahbaz, Adam Ali Husseinat +3
Agentic artificial intelligence systems, capable of autonomous perception, planning, tool use, and multi-step action, are increasingly proposed for critical engineering domains whe…
Causal--Structural Dynamic Graph Learning for Online Transient Stability Trajectory Prediction in Power Systems
Ibrahim Shahbaz, Omar Al-Refai, Isaac Lagoy +3
Power systems consist of dynamically coupled generators, motivating the use of Graph Neural Networks (GNNs) for online transient stability prediction. Traditional GNN frameworks ar…
Inertia-Informed Federated Learning Control Framework for Distributed Smart Grid Resilience
Ibrahim Shahbaz, Omar Al-Refai, Eman Hammad
Resilient-by-design smart grid control demands frameworks capable of maintaining stability under physical disturbances and communication failures, without reliance on centralized c…
Federated Physics-Grounded Reinforcement Learning for Distributed Stability Control in Smart Grids
Omar Al-Refai, Ibrahim Shahbaz, Adam Ali Husseinat +1
Transient stability control in smart grids requires rapid post-fault damping of generator frequency and rotor angle deviations to prevent cascading failures. This paper proposes Fe…
G-PIFNN: A Generalizable Physics-informed Fourier Neural Network Framework for Electrical Circuits
Ibrahim Shahbaz, Mohammad J. Abdel-Rahman, Eman Hammad
Physics-Informed Neural Networks (PINNs) have advanced the data-driven solution of differential equations (DEs) in dynamic physical systems, yet challenges remain in explainability…
An Interpretable Federated Learning Control Framework Design for Smart Grid Resilience
Ibrahim Shahbaz, Eman Hammad, Abdallah Farraj
Power systems remain highly vulnerable to disturbances and cyber-attacks, underscoring the need for resilient and adaptive control strategies. In this work, we investigate a data-d…