[DataLAB | AI & Data: Cyber & Business Analytics]

***** "In God we Trust. All others must bring DATA."***** - William Edwards Deming

Welcome to this global research platform, specifically designed to support potential students and young researchers exploring cutting-edge research in the broad field of AI & Data - Cyber, Business Analytics & SMEs. Key Themes:

• AI/Data-Driven Technologies for Optimization, Automation & Intelligence
• Advancing Cyber Security applications with AI & Data
• Business Analytics, Transformation & SMEs applications with AI/Data-Driven

As AI and data-driven technologies continue to reshape today's business, e.g., Small and medium-sized enterprises (SMEs), and cybersecurity landscape, it is crucial to understand how these emerging technologies operate, their potential impact, and the future research opportunities they present.
The goal is to provide a collaborative environment where students and early-career researchers can explore core AI and Machine Learning algorithms, data-driven modeling techniques, emerging trends, and hands-on experiments with real-world cyber and business datasets.
This platform also offers relevant resources and research guidance, when needed, to help bridge the gap between theoretical understanding and practical application, and to support the development of innovative solutions.

[People - Students/Researchers/Collaborators - National/International]

• Dr. Iqbal H. Sarker [Adviser]

  [Short Bio] Dr. Iqbal H. Sarker received his Ph.D. in Computer Science from Swinburne University of Technology, Australia. He is currently a Research Fellow at Edith Cowan University (ECU), Australia. Prior to this, he worked as a Postdoctoral Fellow at the Cyber Security Cooperative Research Centre (CRC) in association with ECU, as part of an academia–industry collaboration involving CSIRO Data61. He is also an Adjunct Fellow at DigiSAS Lab, University of Technology Sydney (UTS), Australia, and Institute of Computer Science and Digital Innovation, UCSI University, Malaysia. His research focuses on AI & Data - Cyber, Business Analytics & SMEs. He has authored over 100 peer-reviewed publications in leading journals and conferences published by renowned publishers such as Nature, Elsevier, Springer, IEEE and ACM. 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 recognised by ScholarGPS and listed among the world's top 2% most-cited scientists, published by Elsevier and Stanford University, USA. (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!

[Note: After selecting their topic, interested students can explore/read more relevant online resources (e.g., Google Scholar, Elsevier, Springer Nature, IEEE Explore, ACM DL, etc.) to enhance their background knowledge.]

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, npj Artificial Intelligence, Nature. (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)
Perspective	Data-Driven & Cyber	Data-Driven Intelligence can Revolutionize Today’s Cybersecurity World: A Position Paper, Springer Nature. (Online Link)
Perspective	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)
Perspective	AI/LLM	LLM potentiality and awareness: a position paper from the perspective of trustworthy and responsible AI modeling, Springer Nature. (Online Link)