• Adjunct Assistant Professor, Electrical & Computer Engineering
  • Affiliated Faculty, Institute for Quantum Science and Engineering (IQSE) at Texas A&M
Mohamed Massaoudi

Research Interests

    • AI and machine learning for cyber-physical systems
    • Smart grid cybersecurity and resilience
    • Deep learning for power system stability
    • Large Language Models and Generative AI
    • Reinforcement learning for autonomous grid control
    • Renewable energy integration
    • Federated learning for energy systems

Awards & Honors

  • Thomas W. Powell '62 and Powell Industries Inc. Fellowship, Texas A&M University, 2024
  • Richard E. Ewing Award for Excellence, Texas A&M University at Qatar, 2024
  • Second Prize Paper Award, IEEE Industry Applications Society, 2024
  • Best Presentation Recognition, IEEE IECON Conference, 2024
  • Outstanding Research Excellence Award, Texas A&M University at Qatar, 2020

Selected Publications

  • Massaoudi, M., Haque, K. A., Davis, K. R., et al. “Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks.” IEEE Open Journal of Industry Applications, 2024.
  • 2. Massaoudi, M., Abu-Rub, H., Ghrayeb, A. “FLACON: A Deep Federated Transfer Learning-Enabled Transient Stability Assessment During Symmetrical and Asymmetrical Grid Faults.” IEEE Open Journal of Industry Applications, 2024.
  • 3. Ez Eddin, M., Massaoudi, M., Abu-Rub, H., Shadmand, M. “Optimum Partition of Power Networks Using Singular Value Decomposition and Affinity Propagation.” IEEE Transactions on Power Systems, 2024.
  • 4. Massaoudi, M., Abu-Rub, H., Refaat, S. S., et al. “Deep Learning in Smart Grid Technology: A Review of Recent Advancements and Future Prospects.” IEEE Access, 2021.
  • 5. Massaoudi, M., Davis, K. R., Haque, K. A. “Analysis and Quantification of Demand Flexibility for Resilient Distribution Networks: A Systematic Review.” IEEE Access, 2025.