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Dr. Faycal Bouhafs is a Senior Lecturer at the School of Systems & Computing , UNSW Canberra . His research focuses on performance and reliability in wireless communication networks, with expertise in programmable networks, 5G/6G architectures, and IoT security. He leads initiatives in radio resource optimization and physical-layer security using software-defined approaches. Research Interests: Dr. Bouhafs investigates: Programmable wireless networks for dynamic resource allocation Beyond 5G/6G infrastructures supporting massive IoT deployments Security frameworks for cyber-physical systems and IoT ecosystems AI-driven optimization of radio access and network management Publication Focus: Recent works (2020-2025) demonstrate strong emphasis on: Software-defined wireless networking (SDWN) for spectrum sharing Physical-layer security via jamming and deep learning 6G resource optimization and IoT scalability Practical implementations using off-the-shelf equipment

• Programmable and software defined wireless networks
• Beyond 5G and 6G communication networks
• Security in Internet of Things
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Associate Professor Hassan Habibi Gharakheili holds a PhD from UNSW Sydney (2015) and BS/MS degrees from Sharif University of Technology (Iran). He is affiliated with the School of Electrical Engineering and Telecommunications at UNSW, focusing on programmable networks (SDN), IoT security, and data-driven systems. His research addresses challenges in enterprise cybersecurity, IoT device behavior analysis, and smart infrastructure optimization. Education: PhD (UNSW), MS/BS (Sharif University) Affiliations: UNSW Sydney, Editorial Board of IEEE TMC Research interests include SDN-based traffic management, IoT anomaly detection, and network policy enforcement. Key contributions include work on MUD profiles for IoT security, DNS encryption analysis, and UAV-assisted data collection. Over 80 peer-reviewed publications across journals/conferences, with patents on network security and IoT monitoring. Advises students like Shuai Zhang. Active in IEEE/ACM conferences and industry collaborations.

• Programmable Computer Networks (SDN)
• Data-Driven Inference Systems (AI)
• Critical Networked Infrastructures (IoT)
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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.

• Cyber Security
• Artificial Intelligence (AI)/Machine Learning (ML)
• Network Security
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