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Marcus Gallagher is an Associate Professor in the School of Electrical Engineering and Computer Science. His research interests are in the foundations of artificial intelligence, including optimisation and machine learning algorithms. He is particularly interested in understanding the relationship between algorithm performance and problem structure via benchmarking. His research includes cross-disciplinary collaborations and real-world applications of AI techniques in areas such as healthcare and computer networks.

Dr Gallagher received his BCompSc and GradDipSc from the University of New England, Australia in 1994 and 1995 respectively, and his PhD in 2000 from the University of Queensland, Australia. He also completed a GradCert (Higher Education) in 2010.

Dr. Azadeh Ghari-Neiat is a Senior Lecturer in Software Engineering at the University of Queensland. Her research sits at the intersection of the Internet of Things (IoT), mobile computing, crowdsourcing, federated learning, and cybersecurity, with a particular focus on building trustworthy, privacy-preserving intelligent systems deployed at scale. Her current work explores federated fine-tuning of large language models (LLMs), enabling collaborative model adaptation across distributed environments without compromising data privacy, with emerging interests in the security and robustness of autonomous AI agents – bridging her long-standing expertise in distributed computing with the evolving challenges of trustworthy generative AI.

She completed her PhD in Computer Science at RMIT University in 2018. Prior to joining UQ, she was a Senior Lecturer at Deakin University, where she received two teaching awards and an innovation award from the School of IT in 2023 in recognition of her excellence in teaching, student engagement, and innovation, and previously held positions at the University of Sydney as a postdoctoral research fellow and casual lecturer.

At UQ, she coordinates COMP2701 (Generative AI) and lectures in DECO3800/7380 (Design Computing Studio 3), supervises postgraduate research students in areas including trustworthy LLM systems, and serves as program convenor of the Master of Software Engineering programs.

Professor Kristen Gibbons is Group Lead of the Children’s Intensive Care Research Program at the Child Health Research Centre, The University of Queensland, Co-Chair of the Australian and New Zealand Intensive Care Society Paediatric Study Group (ANZICS PSG).

Professor Gibbons holds qualifications in mathematics, information technology, biostatistics, and research communication, and completed her PhD in Biostatistics at UQ. Her career has been dedicated to transforming outcomes for critically ill children through the design and delivery of large-scale international clinical trials and the development of innovative digital platforms to support high-quality research.

She has been instrumental in leading landmark studies, including the NITRIC trial, the largest trial ever undertaken in paediatric congenital heart disease surgery. This trial demonstrated no benefit of using nitric oxide during cardiopulmonary bypass, changing clinical practice internationally and influencing guidance from the American Academy of Paediatrics. Alongside this, Professor Gibbons has pioneered a comprehensive clinical trials digital platform now used across more than 20 projects and 10,000 patient records worldwide.

Professor Gibbons’ research spans clinical trial methodologies, epidemiology, machine learning, prediction modelling, and bioethics, with a strong commitment to improving consent practices in paediatric and adult intensive care research. Her leadership has attracted over $22 million in competitive grant funding, including major NHMRC and MRFF awards, and her contributions have been recognised with the UQ Faculty of Medicine Leader of the Future Award (2023) and the Child Health Research Centre Collaborator of the Year Award (2024).

She is also deeply invested in training and mentoring the next generation of clinician-researchers and data scientists, supervising PhD, Masters, and biostatistics students.

Assoc. Prof. Glencross specialises in computer graphics, human-computer interaction, and their application to real-world industry challenges.

Currently serving as the EAIT Deputy Associate Dean Academic (Students), she also leads research in Graphics and Visualisation aimed at enhancing the understanding of complex information. At UQ, her research has been applied to innovative areas such as Renewable Energy, Health and Safety, and Resilience. Her ongoing funded projects focus on designing technology to support decision-making during natural disasters.

With a strong background in industry-oriented research, Assoc. Prof. Glencross's work in computer graphics has been backed by industry contracts and research council funding. Her contributions have had significant commercial impacts across sectors, including computer games, visual effects, displays, mobile phones, and image-based capture technologies.

Previously, she led the technical product management of a Graphics Processor Unit at ARM Ltd (UK), where her work contributed to intellectual property used in mobile handsets. Additionally, she co-founded two UK-based technology startups. As Research Director of Pismo Software, she spearheaded innovation in automated 3D content creation pipelines for Virtual Reality interior design for Yulio Inc. In her role as Director of Research at a smart heating company, she led the development of an advanced intelligent heating system.

An active contributor to the computer graphics community, Assoc. Prof. Glencross serves as the ACM SIGGRAPH Volunteer Development Chair. She is also a member of the steering committee for the ACM PACM journals and an Associate Editor for the Computers & Graphics journal. Her expertise is recognised through her status as a Senior Member of the ACM.

I bring industry and academic experience in working on quantum error mitigation, quantum error correction, and quantum control theory to enable quantum computing demonstrations on hardware. I am currently investigating the feasibility of combining error mitigation and error correction techniques with quantum algorithms at the University of Queensland. My team's recent focus spans quantum kernel methods, quantum Hamiltonian simulations for chemistry and optimization, and analysis of quantum channels and their impact on quantum learning. While my group is a theoretical physics research group, we focus on hardware-aware algorithms design and have close partnerships with superconducting qubit experimental platforms at UQ and IBM, with supporting classical computational compute capability at Pawsey Sentonix through NCMAS. I co-lead the quantum computing workstream with Prof. Sally Shrapnel for the Queensland Digital Health Center; I work closely with Prof. Eleanor Rieffel quantum algorithms aligned with the work of the newly established Queensland Decarbonization Alliance and I lead the Asia Pacific Hub of IBM Quantum's Industry Working Group for Healthcare and Lifesciences. Prior to this, I worked on execution of dynamic circuits for error mitigation and quantum error correction applications at IBM Quantum (US) for three years. My work resulted in 3 patents and being recognised as one of IBM Research’s Top Technical Contributors in 2023 globally. I have also designed classical algorithms for noise filtering and prediction for trapped ions at the Quantum Control Laboratory in the University of Sydney, winning ARC EQUS inaugural Director’s Medal in Australia in 2019. QDA is hiring a postdoc position in Quantum Algorithms (https://lnkd.in/e9jZQUEt) and funning two Ph.D positions: Robust Quantum Algorithms for Decarbonisation Applications (https://lnkd.in/gQ3S6bjY) & Distributed Quantum-Enhanced Algorithms (https://lnkd.in/gV7z4EQj)

Dr. Thilina Halloluwa is a Teaching-Focused Lecturer in Human-Centred Computing at the University of Queensland. A SEDA-accredited educator with academic and industry experience, his expertise is in Human-Centred Software Engineering, a field where he combines his passion for technology, learning, and well-being.

His work focuses on how software systems shape human behaviour, decision-making, agency, and wellbeing, particularly as AI becomes more deeply embedded in everyday tools and professional practice. As an educator, he is committed to designing engaging, authentic learning experiences that help students connect software engineering theory with real-world practice. His broader academic interests include responsible technology design, AI-assisted programming, human-centred computing, and the development of software systems that are not only technically effective, but genuinely fit for human purpose.

Thilina holds a PhD in Human-Computer Interaction from the Queensland University of Technology and a Bachelor’s degree in Computer Science from the Sri Lanka Institute of Information Technology. Prior to joining UQ, he lectured at the University of Sydney and served as a Senior Lecturer at the University of Colombo, where he led large-scale teaching and digital transformation initiatives.

Dr Anthony Halog: Expert in Circular Economy, Life Cycle Thinking, and Sustainable Systems

Dr. Anthony B. Halog is a professor at the University of Queensland specialising in circular economy, sustainability engineering, industrial ecology, and life cycle assessment (LCA/LCSA). His current work focuses on designing low-carbon, net-zero, and resource-efficient systems to address climate change, waste reduction, and sustainable development.

Dr. Halog works across energy, materials, food, waste, and policy systems, applying systems thinking, life cycle sustainability assessment, digital twins, and artificial intelligence for sustainability. His research helps governments, industries, and communities make evidence-based decisions that reduce emissions, improve resource efficiency, and avoid unintended environmental impacts.

A core focus of his work is transforming linear value chains into circular value chains, supporting green hydrogen, bioenergy, circular bioeconomy, agricultural waste valorisation, waste-to-energy, and sustainable materials. These solutions contribute to decarbonisation, climate resilience, sustainable supply chains, and the green economy.

Key areas of expertise

• Circular economy and industrial ecology

• Life cycle assessment and sustainability metrics

• Green hydrogen, bioenergy, and clean energy transitions

• Sustainable waste management and circular bioeconomy

• Systems modelling, AI-enabled tools, and sustainability policy

Dr. Halog collaborates with policymakers, industry partners, SMEs, and Indigenous communities in Australia and internationally to deliver practical climate solutions and support the transition to decarbonised circular economies.

I undertake multi-disciplinary collaborative research developing mathematical, computational and visualisation approaches and techniques that facilitate the research and education in animal and plant systems.

My major research theme is development of mathematical, computer graphics and simulation approaches and techniques that facilitate the study of genetics, physiology, morphogenesis and ecology at the scale of cells, individual plants and insects and their components. These developments in computational biology are being used to increase our understanding of the dynamics of morphogenesis, and as a tool in applied research and education.

Software Engineering. Ian's research interests are in formal methods for software development.

Errors in a compiler for a programming language can generate errors in the myriad of programs they compile. Our research is looking at verifying optimisation phases of a compiler.

Concurrent programs are difficult to reason about due to the interleaving of execution of concurrent threads leading to an explosion of possible execution sequences. Our research is developing techniques for rely/guarantee reasoning about concurrent programs.

Both the above research strands make use of the Isabelle/HOL theorem prover.

Dr Leah Henrickson is a Senior Lecturer in Digital Media and Cultures at the University of Queensland. She is the author of Reading Computer-Generated Texts (Cambridge University Press, 2021) and other peer-reviewed articles about how we understand text generation systems and output, artificial intelligence, and digital media environments. Dr Henrickson also studies digital storytelling for critical self-reflection, pedagogy, community building, and commercial benefit. She is the author of Digital Storytelling: An Introduction (Polity, 2025).

Dr Henrickson serves as the School of Communication and Arts' Deputy Director, Teaching and Learning. She is also an elected non-professorial member of the University of Queensland's Academic Board, and a nominated member of the Academic Board's Digital Learning Sub-Committee. She is an elected member of the Board of Directors for the Society for the History of Authorship, Reading and Publishing (SHARP) and the Executive Committee of the Australasian Association for Digital Humanities (aaDH), and serves on the Editorial Boards of New Review of Hypermedia and Multimedia and Anthem Press' 'Anthem Studies in Book History, Publishing and Print Culture' series.

Dr Henrickson is especially keen to collaborate on projects involving digital methods and media, hermeneutics, histories of communications media, and unconventional text production and dissemination.

MBChB FRCA FANZCA FFICM PhD

Helen Huang is a Professor and the Discipline Leader for Data Science in the School of EECS at The University of Queensland. She received her BSc degree from Department of Computer Science, Tsinghua University, China, and her PhD in Computer Science from School of EECS, The University of Queensland in 2001 and 2007 respectively. Helen's research interests mainly include multimedia indexing and search, computer vision, recommender systems, social data analysis and knowledge discovery. She has published 200+ papers in prestigious venues, and has served as an Associate Editor for The VLDB Journal, ACM Computing Surveys, ACM Transactions on Information Systems (TOIS), IEEE Transactions on Multimedia (TMM), Pattern Recognition Journal, etc and also a member of the VLDB Endowment Board of Trustees. Helen has been elevated to IEEE Fellow for her contributions to multi-modal data management and ACM Fellow for contributions to large-scale multimedia content understanding, indexing and retrieval.

Helen Huang has received 2016 Chris Wallace Award from Computing Research and Education (CORE) Australasia for a notable breakthrough or a contribution of particular significance in Computer Science, and Women in Technology (WiT) Infotech Research Award 2014, Queensland. She was also a recipient of the Excellence in Higher Degree by Research Supervision Award, University of Queensland, 2018.

Prof Jadwiga Indulska's research interests are in: autonomic and context-aware pervasive/ubiquitous systems (self-adapting computer systems), wired and wireless computer networks, and interoperability of heterogeneous distributed systems

She received her PhD from AGH University of Science and Technology in Krakow in 1985. Her current research projects are in the fields of:

• Autonomic, context-aware pervasive/ubiquitous systems, i.e. self-adapting computer applications which can (i) provide seamless computing over a variety of computers and computer networks, and (ii) adapt to the current context of users and their tasks.

• Communication protocols for computer networks (Internet protocols and protocols for wired networks, wireless networks, heterogeneous wired/wireless networks and sensor networks).

Marta Indulska is a Professor of Business Information Systems and Director of Research at the UQ Business School, The University of Queensland, Australia. She is also the Director of Research at the ARC Training Centre for Information Resilience, and a member of the UQ Business School's Emerging Technology Research Hub. She teaches on topics related to the use and management of Information Systems and Information Technology in business, specifically with a focus on increasing operational efficiency and effectiveness. In 2017, she was a recipient of the UQ Citation for Outstanding Contributions to Student Learning. Marta has a background in Computer Science, having obtained her Computer Science doctorate degree in 2004. Her main research interests include conceptual modelling, business process management and open innovation. She has published over 100 fully refereed articles in internationally recognised journals and conferences, and has contributed several chapters to published books. Her research has been funded through several competitive grants, including ARC Discovery. Marta has also worked with organisations in the retail, consulting and non-profit sectors to provide guidance on a variety Information Technology topics.

I am a computational biologist with a centre-wide research role in the ARC Centre of Excellence for Plant Success in Nature and Agriculture, based here at UQ. I spend my time researching new computational techniques for predicting complex quantitative traits by integrating multiple layers of 'omics data (amongst dozens of other things!).

Areas of interest:

• Machine Learning, AI and high performance computing to learn and exploit functional connectivity in biological data
• Gene Expressions networks
• Multiplex networks, information propagation and perturbation
• Genomic Prediction

My goal is to aid crop and forestry breeders in selecting parental lines more accurately, which gives us a pathway to improving certain plant species. I also spend time developing new data analysis techniques that are being applied to human disease and conditions such as Autism and substance addiction.

David completed his PhD at Australian National University in 2017, focusing on the genome-wide basis of foliar terpene variation in Eucalyptus. He then undertook a postdoc at Oak Ridge National Laboratory, a US Dept of Energy lab with a focus on big data. After a stint as a staff scientist at Oak Ridge, David arrived at the Centre of Excellence in 2023 in the role of a Senior Research Fellow.

Dr Hassan Khosravi is an Associate Professor in Data Science and Learning Analytics at The University of Queensland. As a computer scientist by training, he is passionate about the role of artificial intelligence in the future of education. In his research, he draws on theoretical insights driven from the learning sciences and exemplary techniques from the fields of human-centred AI and crowdsourcing to build technological solutions that enhance student learning and experience. His past research and publications have addressed a number of diverse topics such as learning graphical models, statistical-relational learning, social network analysis, cybersecurity and game theory.

Hassan's teaching career includes coordinating 30 different offerings with class sizes ranging from 50 to 700, in 10 distinct courses to a total of approximately 7000 students at three top-ranked institutions: Simon Fraser University (SFU) and The University of British Columbia (UBC) in Canada, and The University of Queensland (UQ) in Australia. He has taught a range of courses including introductory programming courses, data structures and algorithms, artificial intelligence, database management systems as well as graduate-level data science courses. he also leads and teaches into a variety of formal and programs that mentor and foster the next generation of great teachers. These programs cover a wide variety of topics, including student-centred learning, active learning tools and strategies, supporting assessment design and delivery at scale, and enhancing teaching with learning analytics.

Hassan holds a Senior Fellowship with the Higher Education Academy, which has been awarded in recognition of his contributions to effective approaches to teaching and learning as well as successful coordination, support, supervision, management and mentoring of others in relation to learning and teaching.

Jiwon Kim is an Associate Professor in Transport Engineering and the Director of Higher Degree by Research in the School of Civil Engineering at the University of Queensland. She was a DECRA Fellow (2019-2022) sponsored by the Australian Research Council. She joined UQ in 2014 after completing her PhD research at Northwestern University. Prior to joining Northwestern, she worked at Samsung C&T (Engineering & Construction Group). She received Bachelor’s and Master’s degrees in civil engineering from Korea University.

Her research interests broadly encompass the application of Artificial Intelligence and Machine Learning (AI/ML) to enhance prediction, automation, and insight generation in transportation and urban mobility. She is passionate about developing intelligent autonomous systems that facilitate real-time traffic management and control, mobility service optimization, and traveller support. Her current research explores the potential of deep learning, reinforcement learning, and other cutting-edge AI/ML approaches to achieve these objectives.

Prospective Students

Please visit the link (https://sites.google.com/view/dsteam/pros-students).

Short Biography

Dr. Dan Dongseong Kim is Deputy Director of UQ Cybersecurity and an Associate Professor (Reader in the commonwealth system) (continuing appointment) in Cyber Security at The University of Queensland (UQ), Brisbane, Australia. Before UQ, he was a faculty member (permanent academic staff; Senior Lecturer 2015-2018, Lecturer 2011-2014) in Cyber Security in the Department of Computer Science and Software Engineering at The University of Canterbury (UC), Christchurch, New Zealand from 2011 to 2018. From 2008 to 2011, he was a postdoc at Duke University, Durham, North Carolina in the US. He was a visiting scholar at the University of Maryland, College Park, Maryland in the US in 2007. His research interests are in Cyber Security and Dependability for various systems and networks. Please visit his research team webpage: https://sites.google.com/view/dsteam/

Publications

• Google Scholars (7900+ citations, h-index: 46, i10-index: 134): https://scholar.google.com/citations?user=dIIYVQkAAAAJ&hl=en
• DBLP (200+ publications): https://dblp.org/pid/k/DongSeongKim.html

Research Focus: Cyber G.A.M.E

• Graphical Models for Cyber Security: Model-based Cyber Security Risk Analysis
• AI for Cybersecurity & Cyber Security for AI: Securing AI systems and Cybersecurity using AI
• Moving Target Defense (MTD): Resilient and Proactive Defence
• Evolving Attacks and Defense Automation: Red team and Blue team Automation and evaluation using AI/LLM

Professional Activities (selected)

• Associate Editor, IEEE Communications Surveys and Tutorials (impact factor: 33.84 (2022-2023), #1 impact factor among all the IEEE journals), 2021 - present.
• Editorial Board Member, Elsevier Computers and Security (impact factor: 5.6 (2023)), 2019 - present.
• Editorial Board Member, Elsevier Computer Networks (impact factor: 5.6 (2023)), April 2022 - present.
• An Elected Member of the IFIP WG 10.4 on Dependable Computing and Fault Tolerance (2021 onwards).
  • The IFIP WG 10.4 consists of over 60 experts in the field of fault-tolerance, dependable and secure computing.
• Steering committee member of IFIP/IEEE DSN, 2021-2025.
• Steering committee Chair of IEEE PRDC, 2022-present.
• Steering committee member of IEEE PRDC, 2019-present.
• TPC member of international conferences including IFIP/IEEE DSN, SRDS, ISSRE, ICDCS, etc.

Selected publications

• Securing End-to-End Reinforcement Learning-Driven Autonomous Driving: A Control Command Utility-based Intrusion Response System. IEEE Transactions on Intelligent Vehicles, 2025 [impact factor: 14.3]
• LAGER: Layer-wise Graph Feature Extractor for Network Intrusion Detection, IEEE/IFIP DSN 2025 [CORE A]
• Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey, IEEE Communications Surveys & Tutorials [Impact factor in 2021: 33.84]
• Toward Proactive, Adaptive Defense: A Survey on Moving Target Defense, IEEE Communications Surveys & Tutorials 2020 [Impact Factor 2018-19: 22.973]
• A Survey on Threat Situation Awareness Systems: Framework, Techniques, and Insights, ACM Computing Surveys, 2022 [Impact Factor 2021-22: 10.282, ranked 4/137 in Computer Science Theory & Methods]
• Evaluating the effectiveness of shuffle and redundancy MTD techniques in the cloud. Computers & Security (2021) [Impact factor: 4.438]
• Threat-Specific Security Risk Evaluation in the Cloud. IEEE Trans. Cloud Comput. 9(2): 793-806 (2021) [Impact factor: 4.714]
• Dynamic Security Metrics for Measuring the Effectiveness of Moving Target Defense Techniques, Computers & Security, Elsevier, 2018 [Impact factor: 4.438]
• Assessing the Effectiveness of Moving Target Defenses using Security Models. IEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2016. [CORE Rank A, Impact factor: 6.404]
• Recovery from software failures caused by Mandelbugs. IEEE Transactions on Reliability, 2016. [CORE Rank A, Impact factor: 2.79]
• Scalable Security Models for Assessing Effectiveness of Moving Target Defenses, IEEE/IFIP DSN 2014 [CORE Rank A*]
• Sensitivity Analysis of Server Virtualized System Availability. IEEE Transactions on Reliability, 61(4): 994-1006, 2012. [CORE Rank A, Impact factor: 2.293]
• Scalable Optimal Countermeasure Selection using Implicit Enumeration on Attack Countermeasure Trees, IEEE/IFIP DSN 2012 [CORE Rank A*]

Research Sponsors (past and current)

• NSF (US), IBM T.J. Watson (US), US Army Research Lab./DEVCOM-Pacific (US), NEC (Japan), Tait Comm. (NZ), MBIE (NZ), NPRP (Qatar), ADD (Republic of Korea), NRF (Republic of Korea), etc.

Ph.D. graduates (selected)

1. Ke He (Ph.D., University of Auckland, May 2024, co-supervisor): Adversarial Attacks, Defences and Visualisation for AI-based NIDS. (Lecturer at The University of Canterbury, New Zealanad).

2. Kok Onn Chee (Ph.D., University of Queensland, Jan 2024: Principal Advisor): Security Modelling and Analysis of Internet of Things against Evolving Attacks.

3. Minjune Kim (Ph.D., University of Queensland, 2023: Principal Advisor): Security and performance evaluation of software defined networking adopting moving target defenses (Senior Research Engineer at CSRIO's Data61, Australia).

4. Dilli P. Sharma (Ph.D., University of Canterbury, 2020; senior supervisor at UC, -> co-supervisor at UQ): Software-defined networking based moving target defenses. (Postdoc at U. of New Brunswick, Canada -> Postdoc at the University of Toronto, Canada -> Postdoc, York U., Canada).

5. Taehoon Eom (Ph.D., 2020, KAU, Korea, co-supervisor): Security modeling and analysis for performance enhancement in software defined network (Researcher at KAU-> Research Professor at KAU -> Artificial Intelligence Industry Cluster Agency (AICA), South Korea).

6. Hooman Alavizadeh (Ph.D., Massey University, NZ, 2019, co-supervisor): Effective Security Analysis for Combinations of MTD Techniques on Cloud Computing (a Postdoc, Massey University -> Postdoc at UNSW Canberra->Lecturer at U of Sydney-> Lecturer (continuing academic staff), La Trobe University, Australia).

7. Kieran Morris (Ph.D., ECE, University of Canterbury, NZ, 2019, co-supervisor): Reliability and resilience evaluation of distribution automation (first employment: Tait communications, NZ-> Noted Ltd -> Transpower, NZ).

8. Simon (Enochson) Yusuf (Ph.D., Computer Science, NZ, University of Canterbury, Dec 2018, senior supervisor): Dynamic Cyber Security Modeling and Analysis (Postdoc at UQ-> Lecturer (continuing academic staff) at Federal University Kashere (FUK), Gombe, Nigeria -> Lecturer at Whitecliffe College, New Zealand. )

9. Mengmeng Ge (Ph.D., Computer Science, University of Canterbury, 2018; senior supervisor): Graphical security modeling and assessment for the Internet of things (Senior Lecturer, Monash University, Australia).

10. Iman Elmir (Ph.D., Hassan 1st Univ. Morocco, 2017, co-supervisor): Security Modeling and Analysis of Intrusion Tolerant Data Centers

11. Jin B. Hong (Ph.D., Computer Science, University of Canterbury, April 2015, senior supervisor): Scalable and Adaptable Security Modeling and Analysis. (First employment: Postdoc, UC, NZ -> Lecturer, then Senior Lecturer in Cybersecurity at U of Western Australia)

12. Nguyen Tuan Anh (Ph.D., August 2015, KAU, co-supervisor): Availability Modeling and Analysis of Data Center Systems using Stochastic Reward Nets. (Postdoc, Kunkuk University, South Korea -> an Academic Research Professor, Kunkuk University, South Korea -> Viettel Group, Vietnam -> Director of Robot Software and Control, VinDynamics)

Cyber Security Research Experience

Dan Dongseong Kim has been working on various topics in computer and network security since 2001. Dan started his research with crypto algorithms design, implementation, and testing for hardware devices such as FPGA/ASICs. Then, he worked on machine learning/data mining approaches for (host-based, network-based) intrusion detection from 2001 onward. His master's thesis was a machine learning (ML)-based network intrusion detection. He worked on various computer and network security topics such as an intelligent SIEM (it was called enterprise security management at that time), authentication protocols for RFID systems, security and privacy for Wireless Sensor Networks (WSNs), etc. His Ph.D. topics were security and privacy for WSNs. He spent one year as a visiting scholar at The University of Maryland (UMD), College Park, Maryland in the US in 2007 under the supervision of Prof. Virgil D. Gligor.

He started working on dependability more seriously in addition to Cyber Security in 2008 when he started his postdoc research at Duke University under the supervision of the Hudson Chaired Professor Kishor S. Trivedi. He worked on research projects funded by the US NSF, NEC Japan, and IBM T.J. Watson in the area of dependability (availability/performance) of data centers/cloud computing and cybersecurity modeling & analysis.

Since he became a faculty member at The University of Canterbury, New Zealand in August 2011, he explored deeply the area of graphical models for cybersecurity, metrics, measurement, and efficient evaluation methods for automated cybersecurity modeling and analysis and applied those key ideas to Cloud computing, Internet of Things (IoT), Moving Target Defenses (MTD), cyber deception, and automated cyber-attacks generation. He has focused more on practical adversarial machine learning attacks and robust defence in network intrusion detection systems for IoT and autonomous vehicles since he joined the UQ in 2019. He worked with diverse groups of people from various countries including Australia, Bangladesh, Brazil, China, Germany, Hong Kong, India, Iran, Italy, Japan, Saudi Arabia, South Korea, Mongolia, Morocco, Malaysia, Nepal, New Zealand, Nigeria, Pakistan, Qatar, USA, UK, and Vietnam.

Academic Genealogy

As for his academic genealogy, his Ph.D. thesis advisor was

• Jong Sou Park (Pennsylvania State University, Ph.D., 1994); his one was
• Paul Thomas Hulina (Pennsylvania State University, Ph.D., 1969); then it runs back through
• Jon Gustav Bredeson (Northwestern University, Ph.D., 1967),
• Seifollah Louis Hakimi (The University of Illinois at Urbana-Champaign (UIUC), Ph.D., 1959),
• Mac Van Valkenburg (Stanford University, Ph.D., 1952),
• Oswald Garrison Villard, Jr. (Stanford University, Ph.D., 1949),
• Frederick Emmons Terman (widely credited as being the father of Silicon Valley) (Massachusetts Institute of Technology (MIT), 1924, Sc.D.) and
• Vannevar Bush (Jointly Harvard/MIT, D. Eng., 1916) to
• Arthur Edwin Kennelly (Professor at Harvard/MIT) (who was working in Thomas Edison's West Orange Laboratory from December 1887 to March 1894) and Dugald C. Jackson.

His postdoc advisor is Professor Kishor S. Trivedi (UIUC, Ph.D., 1974) who is a Life Fellow of IEEE and the Hudson Distinguished Professor of Electrical and Computer Engineering at Duke University, USA. Please visit the academic tree from Duglad C. Jackson up to the ancestors at the academic tree (link).