Upcoming PhD Opportunities in Australia (With Scholarship)
*** General Requirements for International Candidates ***(i) Bachelor/Masters with Good Result/GPA;
(ii) Masters by Research/Thesis;
(iii) Few Good Ranked Publications in relevant areas as a LEAD author;
(iv) A Research proposal
(v) Others like Good Programming/Coding skills and IELTS.
Contact Email to send CV: [m.sarker@ecu.edu.au]
Web Profile (Australia): Iqbal H. Sarker (click here)
[DataLAB Research | AI/XAI & Data-Driven : Cybersecurity]
Welcome to this global research platform, specifically designed to support potential students and young researchers exploring cutting-edge research in the broad field of Cybersecurity, Artificial Intelligence (AI) and Data-Driven Technologies . As AI/Data-driven technologies continue to transform the cybersecurity landscape, it is crucial to understand how these advanced techniques function and ensure their decisions are transparent, explainable, and trustworthy.
The goal is to provide a collaborative space where students and young researchers can explore key concepts of AI/ML algorithms, data-driven modeling, current trends, experiments with real-world cybersecurity datasets, and develop innovative solutions. To achieve these goals, this platform supports relevant resources as well as research guidance (when needed), to help bridge the gap between theory and practical applications.
[People - Students/Researchers/Collaborators - National/International]
- Dr. Iqbal H. Sarker [Adviser]
[Biography] is a Research Fellow at the Centre for Securing Digital Futures, Edith Cowan University (ECU), Australia. He earned his Ph.D. in Computer Science from Swinburne University of Technology in Melbourne, Australia. He also worked as a Postdoctoral Fellow at the Cyber Security Cooperative Research Centre in association with ECU, through an academia-industry collaboration including CSIRO Data61, Australia. He is also an Adjunct Fellow at the School of Computer Science, University of Technology Sydney (UTS), Australia. His professional and research interests include Cybersecurity, AI & Machine Learning, Digital Twin, Data-Driven, Business Analytics and SMEs.
He has published 100+ Journal and Conference papers in various reputed venues published by Elsevier, Springer Nature, IEEE, ACM, Oxford University Press, etc. He is the lead author of two Springer books: `Context-Aware Machine Learning and Mobile Data Analytics' and `AI-Driven Cybersecurity and Threat Intelligence'. Dr. Sarker has also been listed among the world's top 2% most-cited scientists, published by Elsevier and Stanford University, USA.
In addition to his research work and publications, Dr. Sarker is involved in several research engagement and leadership roles, such as the Journal editorial board, international conference program committee, student supervision, visiting scholar, and national-international collaboration. He also has some teaching experience relevant to his research areas. He is a member of ACM, IEEE, and the Australian Information Security Association (AISA).
(ORCID Link) - [National/International Collaborators]
- [Students/Young Researchers]
- [Academic-Industry Professionals]
[Some Helpful Resources for the Students/Young Researchers - Published by Sarker et al.
The publications listed below may assist Students to select their Research/Thesis work. So you can read your preferred one and find out your interested Research TOPIC/ Issues/ Questions/ Contributions and enjoy your work!
| Type | Major Domain | Sample Paper to Read and Select your Interested Topic for Research |
|---|---|---|
| Journal | Business Analytics & SMEs | SME-TEAM: Leveraging Trust and Ethics for Secure and Responsible Use of AI and LLMs in SMEs. (Online Link) |
| Journal | Digital Twin & CyberAI | Explainable AI for cybersecurity automation, intelligence and trustworthiness in digital twin: Methods, taxonomy, challenges and prospects (24 pages), ICT Express, Elsevier, South Korea. (Online Link) |
| Journal | Critical Infrastrucutre & CyberAI | Multi-aspect rule-based AI: Methods, taxonomy, challenges and directions towards automation, intelligence and transparent cybersecurity modeling for critical infrastructures, Elsevier, USA. (Online Link) |
| Journal | Data Science | Data science and analytics: an overview from data-driven smart computing, decision-making and applications perspective (22 pages), SN Computer Science, Springer Nature, Germany. (Online Link) |
| Position | Data-Driven & Cyber | Data-Driven Intelligence can Revolutionize Today’s Cybersecurity World: A Position Paper, Springer Nature. (Online Link) |
| Position | Human-AI Teaming & Cyber | AI Potentiality and Awareness: A Position Paper from the Perspective of Human-AI Teaming in Cybersecurity, Springer Nature. (Online Link) |
| Journal | Machine Learning Algorithms | Machine Learning: Algorithms, Real-World Applications and Research Directions (21 pages), SN Computer Science, Springer Nature, Germany . (Online Link) |
| Journal | Deep Learning Techniques | Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions (20 pages), SN Computer Science, Springer Nature, Germany . (Online Link) |
| Journal | AI Techniques | Artificial Intelligence (AI)-based Modeling: Techniques, Applications and Research Issues towards Automation, Intelligent and Smart Systems (20 pages), SN Computer Science, Springer Nature, Germany . (Online Link) |
| Position | AI/LLM | LLM potentiality and awareness: a position paper from the perspective of trustworthy and responsible AI modeling, Springer Nature. (Online Link) |
| Perspective | Business and SMEs | SME-TEAM: Leveraging Trust and Ethics for Secure and Responsible Use of AI and LLMs in SMEs . (Online Link) |
[Some Popular Data Sources for Experiments (Publicly Available)]
- https://www.kaggle.com/datasets/
- https://archive.ics.uci.edu/ml/index.php
- https://huggingface.co/datasets/
- https://www.unb.ca/cic/datasets/index.html
- https://paperswithcode.com/datasets/
- https://catalog.data.gov/dataset/
- https://research.google/tools/datasets/
- https://cloud.google.com/datasets/
- https://datasetsearch.research.google.com/




