Tony Jan is a Full Professor and Head of Information Technology leading AI, IT, cloud, games, and cybersecurity programs at Torrens University Australia. Prior to this role, Tony was Associate Professor and Associate/Deputy Head of School at the Melbourne Institute of Technology (5 years) and University of Technology Sydney (10 years) respectively.

Tony specializes in machine learning for cybersecurity/smart digital technologies and has published over 90 high-impact journals and conference articles. Tony received the University academic leadership award (in 2022), research excellence award (in 2023) and SEI global academic excellence award (in 2024). Tony is the Director of the Artificial Intelligence Research Centre at Torrens, focusing on world standard reseasrch in AI innovations. His research has been supported by several grants including ARC discovery and large-scale industry-sponsored grants (over $20m) in the domains of AI and homeland security.

His recent interests are in machine learning for the Internet of Things (IoT) and cybersecurity.

• Alazab, A., Khraisat, A., Singh, S., & Jan, T. (2023). Enhancing Privacy-Preserving Intrusion Detection through Federated Learning. Electronics (Switzerland), 12(16).
• Sulimani, H., Akbar, M. S., Kaiwartya, O., Alghamdi, W. Y., Jan, T., Simoff, S., & Prasad, M. (2022). Reinforcement optimization for decentralized service placement policy in IoT-centric fog environment. Transactions on Emerging Telecom. p.e.4650.

Tony’s research interest includes,

• Federated machine learning for IoT security (e.g., cybersecurity in health services)
• Ensembled machine learning for real-time industry applications (e.g., mission-critical applications such as commercial drones and driverless vehicles)
• Cognitive machines for human-centric computing applications (e.g., AI-enabled augmented reality for future digital society)
• Smart sensor networks for intelligent environment monitoring (e.g., senior citizen home care and homeland security).

Some of the research in smart and cognitive sensor networks for homeland security was supported by ARC discovery and other several major industry-sponsored grants.