Nada Abdalgawad

Nada Abdalgawad is a PhD researcher in Computer Science and Engineering at the University of Michigan, advised by Dr. Valeria Bertacco. Previously, she earned a BSc in Computer Engineering from the American University of Sharjah (AUS), where she published research in security and machine learning. She served as a teaching assistant for hardware/software courses and received institutional awards for teaching and leadership excellence.

Her research focuses on:

• Computer hardware architecture
• Memory system optimization
• Cybersecurity for IoT devices
• Generative adversarial networks

Key publications address:

• Deep learning for cyberattack detection in IoT networks
• Edge-based intrusion detection using autoencoder frameworks

Notable achievements include:

• IEEE Access publication on IoT-23 dataset analysis
• ICIT conference presentation on adversarial autoencoders
• University-level recognition for academic leadership

She maintains an al-folio blog with technical content on academic workflows and MathJax integration.