Siamak Layeghy

Dr. Siamak Layeghy is a Lecturer in the School of Electrical Engineering and Computer Science at The University of Queensland. He holds a PhD in Information Technology and Electrical Engineering from UQ (2018). His research focuses on AI/ML-driven cybersecurity solutions, particularly network intrusion detection systems (NIDS), IoT security, edge learning, and software-defined networking (SDN).

Education:

• PhD in Information Technology and Electrical Engineering, The University of Queensland (2018)

Research Interests:

• Application of ML techniques (Transformers, GNNs, GANs) for network and IoT security
• Edge computing and hardware acceleration (e.g., Edge TPU)
• Domain-invariant NIDS and cross-platform security solutions
• Federated learning and blockchain for collaborative intrusion detection

His work emphasizes explainability, generalization, and real-world deployability of AI models in cybersecurity.

Publications: Over 50 peer-reviewed articles, including high-impact journals like Expert Systems with Applications and IEEE Transactions. Key themes include sensor-based anomaly detection, SDN security, and framework development (e.g., FlowTransformer).

Labs/Teams: Active contributor to the development of open-source frameworks like FlowTransformer and datasets such as NF-CSE-CIC-IDS2018-v3. Collaborates with industry partners on IoT security and edge computing.