Hussain Ahmad

Dr Hussain Ahmad

Assistant Professor (Lecturer)

School of Computer and Mathematical Sciences

Faculty of Sciences, Engineering and Technology

Dr Hussain Ahmad is a Lecturer at the School of Computer and Mathematical Sciences, University of Adelaide, Australia. His research spans Cyber Security, Software Engineering, and Generative AI, with a strong focus on industry-driven innovation and real-world applications. He leads the design and delivery of courses in Cyber Security, Big Data, and Industry Projects, where he fosters strong connections between academic learning and professional practice. He also provides technical guidance and inclusive feedback to students across undergraduate and postgraduate levels, supporting their research and development activities.

Dr Ahmad’s teaching philosophy is built on four key pillars: industry relevance, continuous feedback, clarity and organisation, and currency of content. He aims to bridge academic learning with real-world applications, ensuring students gain skills aligned with industry demands. He values student feedback and uses it to refine and adapt his teaching approach for improved learning outcomes. Dr Ahmad maintains a clear and organised course structure to help students navigate their learning journey effectively. Recognising the fast-paced nature of computer science, he also ensures that course content remains current, equipping students with up-to-date knowledge and tools.

Dr Hussain Ahmad completed his PhD at the University of Adelaide, Australia, where he conducted interdisciplinary research at the intersection of Cyber Security, Software Engineering, and Artificial Intelligence. He led over 15 R&D projects in collaboration with industry and academic partners, resulting in 12 peer-reviewed publications in top-tier conferences and journals, including CORE A* and A-ranked venues. His publications are available on his Google Scholar profile.

Dr Ahmad’s PhD research focused on enhancing the security of command-and-control (C2) systems critical to civil and defence domains. He developed simulation-based methods for C2 network security analysis, performed static and dynamic risk assessments, and designed an integrated risk management framework. Dr Ahmad also developed advanced techniques for software vulnerability detection, assessment, prioritisation, and management, leveraging machine learning, deep learning, and state-of-the-art Generative AI models. In addition, he explored the use of immersive technologies, including augmented reality, virtual reality, and mixed reality, to improve cyber situational awareness and decision-making.

Beyond cyber security, Dr Ahmad made significant contributions to advancing the scalability, resilience, and efficiency of cloud-native microservice architectures. He focused on optimising containerized software systems to support AI-driven, adaptive DevOps practices in modern distributed cloud environments. Leveraging AWS cloud services, Kubernetes orchestration, and dynamic resource management, he designed, developed, and evaluated a suite of self-adaptive auto-scaling frameworks, Smart HPA, ProSmart HPA, and SecureSmart HPA, that enable resource-aware, proactive, and resilient auto-scaling for high-throughput, latency-sensitive workloads.

Industry Collaborations. During his PhD journey, Dr Ahmad engaged in various R&D projects with prestigious industry partners, including the Department of State Development South Australia, Defence Science and Technology Group Australia, Cyber Security Cooperative Research Centre, CSIRO's Data61, Cisco, Surf Life Saving South Australia, Stone & Chalk, Honeywell UK, and SLB (Schlumberger) USA. 

Academic Collaborations. He also collaborated with renowned academic institutions, including Imperial College London, the University of Melbourne, Monash University, Singapore Management University, Zayed University (UAE), National Institute of Technology (India), and State University of New York Polytechnic Institute (USA).

His research interests include Software Engineering, Cyber Security, Cloud Computing, Generative AI, Prompt Engineering, Large Language Models, and Self-Adaptive Systems.

 

  • Journals
    Year Citation
    2025 Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2025). Towards resource-efficient reactive and proactive auto-scaling for microservice architectures. Journal of Systems and Software, 225, 112390.
    DOI Scopus1
    2025 Ahmad, H., Ullah, F., & Jafri, R. (2025). A Survey on Immersive Cyber Situational Awareness Systems. Journal of Cybersecurity and Privacy, 5(2), 26 pages.
    DOI
    2025 Abdulsatar, M., Ahmad, H., Goel, D., & Ullah, F. (2025). Towards deep learning enabled cybersecurity risk assessment for microservice architectures. Cluster Computing, 28(6), 16 pages.
    DOI
    2024 Jayalath, R. K., Ahmad, H., Goel, D., Syed, M. S., & Ullah, F. (2024). Microservice Vulnerability Analysis: A Literature Review With Empirical Insights. IEEE Access, 12, 155168-155204.
    DOI Scopus3
    2023 Ahmad, H., Dharmadasa, I., Ullah, F., & Babar, M. A. (2023). A Review on C3I Systems' Security: Vulnerabilities, Attacks, and Countermeasures. ACM Computing Surveys, 55(9), 192-1-192-38.
    DOI Scopus14 WoS1

  • Conference Papers
    Year Citation
    2024 Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2024). Smart HPA: A Resource-Efficient Horizontal Pod Auto-Scaler for Microservice Architectures. In Proceedings - IEEE 21st International Conference on Software Architecture, ICSA 2024 (pp. 46-57). Online: IEEE.
    DOI Scopus6

  • Preprint
    Year Citation
    2025 Ullah, F., Ye, X., Fatima, U., Akhtar, Z., Wu, Y., & Ahmad, H. (2025). What Skills Do Cyber Security Professionals Need?.
    2025 Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2025). Resilient Auto-Scaling of Microservice Architectures with Efficient
    Resource Management.
    2025 Ahmad, H., & Goel, D. (2025). The Future of AI: Exploring the Potential of Large Concept Models.
    2024 Chopra, S., Ahmad, H., Goel, D., & Szabo, C. (2024). ChatNVD: Advancing Cybersecurity Vulnerability Assessment with Large
    Language Models.
    2024 Ahmad, H., & Goel, D. (2024). Machine Learning Driven Smishing Detection Framework for Mobile Security.
    DOI
    2024 Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2024). Smart HPA: A Resource-Efficient Horizontal Pod Auto-scaler for
    Microservice Architectures.
    2024 Abdulsatar, M., Ahmad, H., Goel, D., & Ullah, F. (2024). Towards Deep Learning Enabled Cybersecurity Risk Assessment for
    Microservice Architectures.
    2024 Jayalath, R. K., Ahmad, H., Goel, D., Syed, M. S., & Ullah, F. (2024). Microservice Vulnerability Analysis: A Literature Review with Empirical
    Insights.
    2024 Ahmad, H., Ullah, F., & Jafri, R. (2024). A Survey on Immersive Cyber Situational Awareness Systems.
    2024 Ahmad, H., Treude, C., Wagner, M., & Szabo, C. (2024). Towards Resource-Efficient Reactive and Proactive Auto-Scaling for Microservice Architectures.
    DOI
    2024 Abbas, F., & Ahmad, H. (2024). Robust Partial Least Squares Using Low Rank and Sparse Decomposition.
    DOI
    2022 Ahmad, H. (2022). "I think this is the most disruptive technology": Exploring Sentiments of ChatGPT Early Adopters using Twitter Data.
    DOI
    2021 Ahmad, H., Dharmadasa, I., Ullah, F., & Babar, M. A. (2021). A Review on C3I Systems' Security: Vulnerabilities, Attacks, and Countermeasures..
  • Awarded an AUD 5,000 Seed Grant by the School of Computer and Mathematical Sciences, University of Adelaide, to initiate foundational research on Agentic AI for software security. (2025)
  • Awarded a Seed-Start grant of AUD 100,000 from the Department of State Development South Australia, to enhance the digital operations of Migrova through AI-driven technology integration. (2024)
  • Awarded three Research Training Program (RTP) Scholarships at the University of Adelaide, which facilitated my doctoral research expenditures.
  1. University of Adelaide Research Scholarship [AUD 88,250] (2022)
  2. Cyber Security CRC Postgraduate Research Scholarship [AUD 75,000] (2022)
  3. School of Computer Science Scholarship [AUD 85,791] (2021)
Term Course Code Course Name Role
Trimester 1, 2025 COMP SCI 7205A Artificial Intelligence and Machine Learning Research Project, Part A Project Supervisor
COMP SCI 7102B Cyber Security Industry Project B Project Supervisor
Semester 1, 2025 COMP SCI 7098 Master of Computing & Innovation Project Project Supervisor
COMP SCI 7100A Research Project Master Computer Science‚ Part A Project Supervisor
Trimester 2, 2025 COMP SCI 7205B Artificial Intelligence and Machine Learning Research Project, Part B Project Supervisor
COMP SCI 7209 Big Data Analysis and Project Lecturer and Course Coordinator
COMP SCI 7328 Concepts in Cyber Security Lecturer and Course Coordinator
COMP SCI 7205A Artificial Intelligence and Machine Learning Research Project, Part A Project Supervisor
Semester 2, 2025 COMP SCI 7100B Research Project Master Computer Science, Part B Project Supervisor
COMP SCI 3021 Industry Project in Information Technology Lecturer and Course Coordinator
COMP SCI 3021MELB Industry Project in Information Technology Lecturer and Course Coordinator
Trimester 3, 2025 COMP SCI 7205B Artificial Intelligence and Machine Learning Research Project, Part B Project Supervisor
Trimester 1, 2024 COMP SCI 7101B Cyber Security Research Project B Project Supervisor
Semester 1, 2024 COMP SCI 7100A Research Project Master Computer Science, Part A Project Supervisor
Semester 2, 2024 COMP SCI 7100B Research Project Master Computer Science, Part B Project Supervisor
COMP SCI 3021 Industry Project in Information Technology Project Supervisor
Trimester 2, 2023 COMP SCI 7101A Cyber Security Research Project A Project Supervisor
Trimester 3, 2023 COMP SCI 7101A Cyber Security Research Project A Project Supervisor
COMP SCI 7101B Cyber Security Research Project B Project Supervisor

Teaching Philosophy

My teaching philosophy is primarily driven by the following four features.

  • Industry relevance. I keep an eye on industry needs and aim to align my teaching in a way that best relates the content to the industry needs. This helps to enable the students to develop knowledge and learn skills that are directly used in the industry.
  • Feedback-driven. I am always keen to learn from students how best the course can be taught to convey the maximum value to the students. Also, I observe the students' responses throughout and adjust the path of teaching continuously.
  • Organized and well-defined. I believe that each aspect (e.g., lecture, assignments, evaluation rubrics, etc.) of teaching should be entirely organized and clear. This helps students to plan and follow the course clearly and neatly right from the beginning.
  • Up-to-date. Computer science is a field that evolves quite rapidly. I aim to keep the content of the course as up-to-date as possible. This helps students to not stick to content that is no longer used in the field. Rather, the students learn content that they can directly use in the field. 

  • Other Supervision Activities
    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2025 - ongoing Principal Supervisor Agentic AI for Software Security The University of Adelaide Master of Artificial Intelligence and Machine Learning Master Full Time Joel Thomas, Asrul Arifin, Rohan Kosuri, Kamalesh Gunasekaran, Deepak Vasudevan
    2025 - ongoing Principal Supervisor Optimizing Prompt Engineering through Evolutionary Computation The University of Adelaide Master of Computer Science Master Full Time Zijie Luo, Gaurav Singh, Jiyin Shao, Aditya Karthully, Fuliang Zhang
    2025 - ongoing Principal Supervisor Evaluating the Performance of Large Language Models The University of Adelaide Master of Computer Science Master Full Time Durga Chodavarapu, Subin Santhosh, Yinzhi Tian, Tuhin Anand, Samman Hossain
    2025 - 2025 Principal Supervisor Horizontal Pod Auto-scaling of Software Systems Using Multi-Metric Optimization The University of Adelaide Master of Computing and Innovation Master Full Time Han-Hsien Lei, Hao Jiang, Linxin Qi, Feng Cao, Wu-Yang Wen
    2025 - 2025 Principal Supervisor A Self-Adaptive Framework for Software Security The University of Adelaide Master of Computing and Innovation Master Full Time Yiqi Wang, Enze Li, Enjian Mai, Yansong Zhang, Mutian Qiu
    2025 - 2025 Principal Supervisor A Comparative Study of AI Models for Recommendation Systems The University of Adelaide Master of Computing and Innovation Master Full Time Manhong Chen, Zihan Luo, Ziyan Zhao, Jianing Dang, Jianghao Jin
    2025 - ongoing Principal Supervisor Adaptive Cyber Deception for Enhancing Enterprise Network Security The University of Adelaide Master of Artificial Intelligence and Machine Learning Master Full Time Pemba Sherpa, Majdi Almistehi, Menuja Mabotuwana
    2025 - ongoing Principal Supervisor AI for Scalable Microservice Architectures The University of Adelaide Master of Artificial Intelligence and Machine Learning Master Full Time Mohammed Ribin, Akash Kumar
    2024 - 2024 Principal Supervisor AI-Driven Migration Services in Australia The University of Adelaide Bachelor of Information Technology Honours Full Time Ho Yin LI, Jiazhi Chen, Kun Fai Lei, Xiao Han, Yiu Lung Tam, Zhenyang LI
    2024 - 2024 Principal Supervisor Advancing Cybersecurity Vulnerability Assessment with Large Language Models The University of Adelaide Master of Computer Science Master Full Time Shivansh Chopra
    2023 - 2024 Principal Supervisor Microservice Vulnerability Analysis: A Literature Review With Empirical Insights The University of Adelaide Master of Cyber Security Master Full Time Raveen Kanishka Jayalath
    2023 - 2023 Principal Supervisor Towards Deep Learning Enabled Cybersecurity Risk Assessment for Microservice Architectures The University of Adelaide Master of Cyber Security Master Full Time Majid Abdulsatar
  • Position: Assistant Professor (Lecturer)
  • Email: hussain.ahmad@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor 4
  • Org Unit: Research Scholars (Positions)
Connect With Me
External Profiles