Shahbaz Khan

Shahbaz Khan is a researcher and Ph.D. candidate in Computing (Cyber Security and AI) at Edinburgh Napier University, UK. He holds B.S. and M.S. degrees in Electronics and Electrical Engineering from NFC IET and HITEC University, Pakistan. He previously served as a Lecturer in Electrical Engineering at HITEC University for eight years. His research focuses on applied cryptography, image encryption, post-quantum cryptography, and intelligent healthcare systems. He is a member of the Centre for Cybersecurity, IoT and Cyberphysical Systems at Edinburgh Napier University.

Education:

• Bachelor of Science (B.S.) in Electronics and Electrical Engineering, NFC Institute of Engineering & Technology (NFC IET), Pakistan
• Master of Science (M.S.) in Electronics and Electrical Engineering, HITEC University, Taxila, Pakistan

Research Interests:

• Image Encryption Techniques (e.g., chaos-based, DNA computing, and hybrid models)
• Post-quantum cryptographic schemes
• Federated learning in healthcare and IoT
• Cybersecurity in industrial IoT and edge computing
• AI-driven medical diagnostics (e.g., EEG-based MDD detection, skin disease classification)

Notable Projects:

• SafeNet: Carnegie-funded project (2024-2025) to enhance IoT network security through robust cryptographic methods.
• Development of encryption algorithms like VisCrypt, PermutEx, and Noise-Crypt for secure image transmission.
• AI models for decentralized EEG-based mental health detection and federated learning in skin disease diagnosis.

Awards: None explicitly mentioned in available texts.

Grants: £13,381 from the Carnegie Trust for the SafeNet project.

Labs/Teams: Active member of the Centre for Cybersecurity, IoT and Cyberphysical Systems at Edinburgh Napier University.