Dr. Ali Jaddoa, PhD, MSc, PGCert, BSc, FHEA

I am a Senior Lecturer in Cyber Security at the University of Roehampton, specialising in cyber security, digital forensics, ethical hacking, and IoT security. My work involves teaching, research, industry collaboration, and supervising postgraduate students.

I hold a BSc, and MSc in Computer Science from Liverpool John Moores University and a PhD in Information Systems from the University of Greenwich, focusing on IoT-edge-cloud computation offloading. My research interests include cyber security, Zero Trust architecture, IoT security, AI-driven threat detection, energy-efficient computing, and cloud security.

Previously, I was a Senior Lecturer in Cyber Security at Canterbury Christ Church University (CCCU), where I taught cyber security and digital forensics, developed course materials, and led quality and partnerships for School of Engineering, Technology and Design. I have also worked on EU H2020 projects such as RESCUER and C4IIoT, contributing to cyber security, IoT, Data orchestration and energy consumption research.

With experience in academia, research, and industry, I am passionate about bridging the gap between theory and practice to advance cyber security education and innovation.

Please email me at [email protected]

• Postgraduate Certificate in Academic Practice – Canterbury Christ Church University, UK (2023–2024)
• PhD in Computing and Information Systems – University of Greenwich, UK (2018–2022)
• MSc in Computer Science – Liverpool John Moores University, UK (2015–2016)
• BSc in Computer Science – University of Babylon, Iraq (2006–2010)

• Computational offloading
• Edge and cloud computing
• Energy-efficient computing
• Machine learning
• Decision support and data orchestration in IoT
• Cybersecurity.  
• Zero Trust 
• AI-based anomaly and intrusion detection

• Estimating the Prevalence of Problematic Opiate Use in Ireland: Public Health Institute (PHI), Liverpool John Moores University (2016)
• RESCUER: First Responder Centered Support Toolkit for Operating in Adverse and Infrastructure-less Environments: University of Greenwich (2019-2022)
• C4IIoT: Cybersecurity 4.0 - Protecting the Industrial Internet of Things: University of Greenwich (2021-2022).
• Repurposing of Retired Electric Vehicle Lithium-ion Batteries through State of Charge Estimation with Deep Learning Techniques, Canterbury Christ Church University (2022-2025)

• Digital Forensics (L7): This module covers the historical and legal aspects of cybercrime, key forensic techniques for data acquisition, analysis, and reporting, and the use of tools like Python and Autopsy. It also explores ethical considerations, evidence handling, and countermeasures against anti-forensic techniques.
• Cyber security(L7):The module incorporates ideas from ethical practice, risk management, legal considerations, and technology-based solutions to address computer security issues.
• Cybersecurity Fundamentals (Level 7): Foundational cybersecurity principles, including threat analysis, risk management, cryptography, network security, and compliance with industry frameworks.
• Computer Forensics and Cybersecurity (Level 5): Digital forensics and cybersecurity principles, including forensic investigation techniques, evidence handling, cybercrime analysis, and implementing robust security measures.
• Advanced Networks (Level 7): Advanced networking topics, including network architecture, protocols, security, and performance analysis.
• Computer Networking (Level 6): In-depth exploration of computer networking, including network design, protocols, routing, and security.
• Fundamentals of Computer Systems (Level 4): Core computer system concepts, encompassing hardware architecture, operating systems, and network fundamentals.
• Computational Thinking (Level 4): Developing problem-solving skills using computational methods, including algorithms, data structures, and applying these techniques across various domains.
• Research Methods (Level 5): Principles of research design, data collection, and analysis in computer science, covering both qualitative and quantitative research methodologies.
• Application Development in C#: Software development fundamentals using C#, encompassing object-oriented programming, GUI design, database integration, and Windows application development.
• Computation Theory (Level 6): Theoretical foundations of computation, including automata theory, formal languages, Turing machines, and computational complexity.
• Advanced Data Structures (Python) (Level 7): Advanced data structures and their implementation in Python, including balanced trees, hash tables, priority queues, and graph algorithms, with an emphasis on performance optimisation.
• Algorithms Design and Analysis (Level 5): Principles of algorithm design, complexity analysis, and optimisation techniques, including strategies like divide-and-conquer, dynamic programming, and greedy algorithms.
• Object-Oriented Programming (OOP) (Level 4): Object-oriented programming concepts using languages like Java and C#, including classes, objects, inheritance, polymorphism, and software design principles.
• Data Structures (Java) (Level 4): Fundamental data structures such as arrays, linked lists, stacks, queues, trees, and graphs, emphasising their implementation and application in Java.
• Computer Graphics (C++) (Level 5): Fundamentals of computer graphics, including 2D and 3D rendering, geometric transformations, and graphical algorithms, with implementation using C++.

Fellow of the Higher Education Academy (FHEA)