Overview
Background
Opportunities for Students
I am keen to supervise motivated postgraduate and PhD students who are passionate about AI, cybersecurity, or networking. My research group offers hands-on projects, including developing AI-driven intrusion detection systems, securing IoT ecosystems, and optimising SDN frameworks. Students will gain experience with state-of-the-art ML tools, collaborate with industry partners, and contribute to high-impact publications. Ideal candidates should have strong programming skills (e.g., Python, C++) and a basic understanding of ML or networking concepts, though enthusiasm and a willingness to learn are equally valued.
Why Join My Group?
My research is inherently interdisciplinary, bridging AI, cybersecurity, and networking to address real-world problems. Students will work on cutting-edge projects with access to UQ’s world-class facilities and opportunities to collaborate with global experts. Whether you’re interested in defending against cyber threats or shaping the future of IoT and SDN, my group provides a dynamic environment to grow as a researcher.
About Me
As a passionate researcher at The University of Queensland, I explore the intersection of Artificial Intelligence (AI) and Machine Learning (ML) with cutting-edge applications in cybersecurity, Internet of Things (IoT), and Software Defined Networking (SDN). My work focuses on developing innovative, real-world solutions to protect digital systems and optimise network performance, mentoring the next generation of researchers to tackle global challenges.
Availability
- Dr Siamak Layeghy is:
- Available for supervision
Qualifications
- Doctor of Philosophy, The University of Queensland
Research interests
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AI/ML for Cybersecurity
I develop advanced intrusion detection systems (NIDS and HIDS) using techniques like Transformers, Generative Adversarial Networks (GANs), and Transfer Learning to detect and mitigate cyber threats in real time.
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Edge Learning and IoT Security
My work focuses on lightweight AI models for resource-constrained IoT devices, enabling secure and efficient edge computing.
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Software Defined Networking (SDN)
I explore network optimisation and programmable data planes (e.g., P4) to enhance Quality of Service (QoS) and constrained routing for next-generation networks.
Research impacts
Research Vision
My research leverages AI and ML to secure and optimise emerging technologies. By combining advanced techniques like Large Language Models (LLMs), Graph Neural Networks (GNNs), and Federated Learning with practical applications, I aim to create robust, scalable systems for network security, edge computing, and programmable networks. My goal is to address pressing challenges in cybersecurity and IoT, ensuring safe and efficient digital ecosystems.
My Google Scholar: https://scholar.google.com.au/citations?user=uB6MlpQAAAAJ&hl=en
Works
Search Professor Siamak Layeghy’s works on UQ eSpace
2014
Journal Article
Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models
Odabaee, Maryam, Tokariev, Anton, Layeghy, Siamak, Mesbah, Mostefa, Colditz, Paul B., Ramon, Ceon and Vanhatalo, Sampsa (2014). Neonatal EEG at scalp is focal and implies high skull conductivity in realistic neonatal head models. NeuroImage, 96, 73-80. doi: 10.1016/j.neuroimage.2014.04.007
2014
Conference Publication
Classification of fetal movement accelerometry through time-frequency features
Layeghy, Siamak, Azemi, Ghasem, Colditz, Paul and Boashash, Boualem (2014). Classification of fetal movement accelerometry through time-frequency features. International Conference on Signal Processing and Communication Systems (ICSPCS), Gold Coast, QLD, Australia, 15-17 December 2014. Piscataway, NJ, United States: IEEE. doi: 10.1109/ICSPCS.2014.7021055
2014
Conference Publication
Non-invasive monitoring of fetal movements using time-frequency features of accelerometry
Layeghy, Siamak, Azemi, Ghasem, Colditz, Paul and Boashash, Boualem (2014). Non-invasive monitoring of fetal movements using time-frequency features of accelerometry. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014), Florence, Italy, 4-9 May 2014. Piscataway, NJ, United States: Institute of Electrical and Electronics Engineers. doi: 10.1109/ICASSP.2014.6854429
2012
Conference Publication
EEG amplitude and correlation spatial decay analysis for neonatal head modelling
Odabaee, Maryam, Layeghy, Siamak, Mesbah, Mostefa, Azemi, Ghasem, Boashash, Boualem, Colditz, Paul and Vanhatalo, Sampsa (2012). EEG amplitude and correlation spatial decay analysis for neonatal head modelling. 11th International Conference on Information Science, Signal Processing and their Applications, ISSPA 2012, Montreal, QC Canada, 2 - 5 July 2012. Piscataway, NJ United States: I E E E. doi: 10.1109/ISSPA.2012.6310679
2012
Conference Publication
A passive DSP approach to fetal movement detection for monitoring fetal health
Khlif, Mohamed Salah H., Boashash, Boualem, Layeghy, Siamak, Ben-Jabeur, Taoufik, Colditz, Paul B. and East, Christine (2012). A passive DSP approach to fetal movement detection for monitoring fetal health. 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), Montreal, Canada, 2-5 July 2012. Piscataway, NJ, Australia: IEEE. doi: 10.1109/ISSPA.2012.6310647
2011
Conference Publication
Time-Frequency Characterization of Tri-Axial Accelerometer Data for Fetal Movement Detection
Khlif, M.S., Boashash, B., Layeghy, S., Ben-Jabeur, T., Mesbah, M., East, C. and Colditz, P. (2011). Time-Frequency Characterization of Tri-Axial Accelerometer Data for Fetal Movement Detection. IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Bilbao, Spain, 14-17 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISSPIT.2011.6151607
2011
Conference Publication
A time frequency approach to CFAR detection
Layeghy, S., Odabaee, M., Khlif, M.S. and Amindavar, H.R. (2011). A time frequency approach to CFAR detection. 11th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT 2011), Bilbao, Spain, 14-17 December 2011. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISSPIT.2011.6151565
Funding
Current funding
Past funding
Supervision
Availability
- Dr Siamak Layeghy is:
- Available for supervision
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Supervision history
Current supervision
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Doctor Philosophy
Enhancing Cyberbullying Detection in Arabic Social Media through Explainable AI and Natural Language Processing: A Human-Centric Approach
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Enhancing the Privacy-Preserving ML techniques with Functional Encryption approach
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Machine Learning for Improving Services and Management of Software Defined Networks
Principal Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
eXtended Management Network System (xNMS)
Associate Advisor
Other advisors: Professor Marius Portmann
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Doctor Philosophy
Exploring the Capabilities of LoRaWAN IoT Technology for Multisensor Data Collection and Analysis
Associate Advisor
Other advisors: Professor Sara Dolnicar, Professor Marius Portmann
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Doctor Philosophy
Towards Practical Machine Learning Based Network Intrusion Detection
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
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Doctor Philosophy
Low-energy LoRaWAN-based automatic and continuous measurement of organisational environmental performance.
Associate Advisor
Other advisors: Professor Sara Dolnicar, Professor Marius Portmann
Completed supervision
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2023
Doctor Philosophy
Deep Learning at the Edge: Exploring in-situ Classification in IoT
Associate Advisor
Other advisors: Professor Marius Portmann
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2023
Doctor Philosophy
The Detection of Network Cyber Attacks Using Machine Learning
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
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2023
Master Philosophy
Graph Representation Learning for Cyberattack Detection and Forensics
Associate Advisor
Other advisors: Associate Professor Marcus Gallagher, Professor Marius Portmann
Media
Enquiries
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