7 papers
Towards Cyber-Physical Cognition: A Unified Ontology-Driven Knowledge Graph for Real-Time Autonomous Grid Operations
Sathvik Sankaranarayanan, Michael Mandulak, Ibrahim Shahbaz +1
Modern power systems and smart grids are often composed of fragmented and heterogeneous data silos, which lack the cohesion needed for effective cross-domain analysis. For this, th…
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…