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Dr Saeed Akhlaghpour is an Associate Professor of Information Systems at UQ Business School. Prior to joining the University of Queensland in 2015, he held academic positions at Middlesex University London (UK), and McGill University (Canada) - where he also obtained his PhD in Management.

Saeed is a Fellow of the Higher Education Academy. He teaches Master of Commerce, MBA, and executive education courses. Previously, he has taught courses such as IT for Business Value, e-Marketing Strategy and Social Media, International Business Environments, and Managing Data & Databases to MBA and undergraduate business students in Brisbane, London, Montreal, and Tehran.

Saeed’s research has been published in top-tier academic outlets including the American Journal of Sociology, Journal of the Association for Information Systems, Journal of Information Technology, Information and Organization, Journal of the American Medical Informatics Association, International Journal of Medical Informatics, International Journal of Information Management, Journal of Business Research, and the Best Paper Proceedings of Academy of Management. His articles are cited in the EU policy documents and have received research and impact awards from the Administrative Sciences Association of Canada, and the Australasian chapter of the Association for Information Systems (AIS).

His research interests include:

• Data protection, privacy and cybersecurity (particularly, organisational response to data breaches, and managing personal health information (PHI))
• Digital health and transformation of healthcare services
• Diffusion and adoption of digital innovations (particularly, management and IT fashions)

Saeed is a Chief Investigator in an Australian Research Council (ARC) funded Linkage Project studying Digital Hospital implementation in Queensland hospitals and health services. He received the UQ Business School Cross Cross-Disciplinary Research Award in 2021.

He is currently a Section Editor of the Australasian Journal of Information Systems, Associate Editor of the Asia Pacific Journal of Information Systems (APJIS), and Editorial Board member of Information and Organization (I&O), International Journal of Medical Informatics, and Journal of Electronic Commerce in Organizations. He co-chairs the Digital Health Care track at the Australasian Conference on Information Systems (ACIS), and the AI in Business & Society track at the International Conference on Information Systems (ICIS) (https://icis2023.aisconferences.org/track-descriptions/#toggle-id-10)

Prof David Ascher is currently an NHMRC Investigator and Director of the Biotechnology Program at the University of Queensland. He is also Head of Computational Biology and Clinical Informatics at the Baker Institute.

David’s research focus is in modelling biological data to gain insight into fundamental biological processes. One of his primary research interests has been developing tools to unravel the link between genotype and phenotype, using computational and experimental approaches to understand the effects of mutations on protein structure and function. His group has developed a platform of over 40 widely used programs for assessing the molecular consequences of coding variants (>7 million hits/year).

Working with clinical collaborators in Australia, Brazil and UK, these methods have been translated into the clinic to guide the diagnosis, management and treatment of a number of hereditary diseases, rare cancers and drug resistant infections.

David has a B.Biotech from the University of Adelaide, majoring in Biochemistry, Biotechnology and Pharmacology and Toxicology; and a B.Sci(Hon) from the University of Queensland, majoring in Biochemistry, where he worked with Luke Guddat and Ron Duggleby on the structural and functional characterization of enzymes in the branched-chain amino acid biosynthetic pathway. David then went to St Vincent’s Institute of Medical Research to undertake a PhD at the University of Melbourne in Biochemistry. There he worked under the supervision of Michael Parker using computational, biochemical and structural tools to develop small molecules drugs to improve memory.

In 2013 David went to the University of Cambridge to work with Sir Tom Blundell on using fragment based drug development techniques to target protein-protein interactions; and subsequently on the structural characterisation of proteins involved in non-homologous DNA repair. He returned to Cambridge in 2014 to establish a research platform to characterise the molecular effects of mutations on protein structure and function- using this information to gain insight into the link between genetic changes and phenotypes. He was subsequently recruited as a lab head in the Department of Biochemistry and Molecular Biology at the University of Melbourne in 2016, before joining the Baker Institute in 2019 and the University of Queensland in 2021.

He is an Associate Editor of PBMB and Fronteirs in Bioinformatics, and holds honorary positions at Bio21 Institute, Cambridge University, FIOCRUZ, and the Tuscany University Network.

Mikael Bodén has a PhD in Computer Science and statistical machine learning from the University of Exeter (UK) but has spent the last decade and a half in biological research environments, including the Institute for Molecular Bioscience/ARC Centre of Excellence in Bioinformatics and the School of Chemistry and Molecular Biosciences, where he is currently located. He is the director of UQ’s postgraduate program in bioinformatics. Mikael Bodén has supervised 7 postdocs from funding he received from both ARC and NHMRC; he has been the primary advisor for 11 PhD and 3 MPhil graduates; he is currently supervising another 6 PhD students in bioinformatics and computational biology. Mikael Bodén collaborates with researchers in neuroscience, developmental biology, protein engineering and bioeconomy to mention but a few, and contributes expertise in the processing, analysis and integration of biological data; this is exemplified by recent publications in Science, Nature Catalysis, Nature Communications, Cell Systems, Nucleic Acids Research and Bioinformatics.

Dr Steffen Bollmann joined UQ’s School of Electrical Imaging and Computer Science in 2020 where he leads the Computational Imaging Group. The Group is developing computational methods to extract clinical and biological insights from magnetic resonance imaging (MRI) data. The aim is to make cutting-edge algorithms and tools available to a wide range of clinicians and researchers. This will enable better images, faster reconstruction times and the efficient extraction of clinical information to ensure a better understanding of a range of diseases. Dr Bollmann was appointed Artificial Intelligence (AI) lead for imaging at UQ’s Queensland Digital Health Centre (QDHeC) in 2023.

His research expertise is in quantitative susceptibility mapping, image segmentation and software applications to help researchers and clinicians access data and algorithms.

Dr Bollmann completed his PhD on multimodal imaging at the University Children’s Hospital and Swiss Federal Institute of Technology (ETH) Zurich, Switzerland.

In 2014 he joined the Centre for Advanced Imaging at UQ as a National Imaging Facility Fellow, where he pioneered the application of deep learning methods for quantitative imaging techniques, in particular Quantitative Susceptibility Mapping.

In 2019 he joined the Siemens Healthineers collaborations team at the MGH Martinos Center in Boston on a one-year industry exchange where he worked on the translation of fast imaging techniques into clinical applications.

Shakes an imaging expert that leads a strong deep learning, artificial intelligence (AI) focused research team interested in medical image analysis and signal/image processing applied to many areas of science and medicine. He received his Ph.D in Theoretical Physics from Monash University, Melbourne and has been involved in applying machine learning in medical imaging for over a decade.

Shakes’ past work has involved developing shape model-based algorithms for knee, hip and shoulder joint segmentation that is being developed and deployed as a product on the Siemens syngo.via platform. More recent work involves deep learning based algorithms for semantic segmentation and manifold learning of imaging data. Broadly, he is interested in understanding and developing the mathematical basis of imaging, image analysis algorithms and physical systems. He has developed algorithms that utilise exotic mathematical structures such as fractals, turbulence, group theoretic concepts and number theory in the image processing approaches that he has developed.

He is currently a Senior Lecturer and leads a team of 20+ researchers working image analysis and AI research across healthcare and medicine. He currently teaches the computer science courses Theory of Computation and Pattern Recognition and Analysis.

Dr Archie Chapman is an Associate Professor in Computer Science in the School of IT and Electrical Engineering.

Archie develops and applies principled artificial intelligence, game theory, optimisation and machine learning methods to solve large-scale and dynamic allocation, scheduling and queuing problems. His recent research has focused on applications of these techniques to problems in future power systems, such as integrating large amounts of renewable power generation and using batteries and flexible loads to provide power network and system services, while making best use of legacy network and generation infrastructure.

Prior to joining UQ, Archie was Research Fellow in Smart Grids at the University of Sydney (2011-2019), and a postdoc fellow at the University of Southampton (2009-2010), where he completed his PhD.

Summary of Research:

• My current research at UQ is as Professor in this School (teaching AGRC3040 Crop Physiology) and as an Affiliate Professor of QAAFI. Since 2020, with full-time appointment at UQ, my research portfolio has included multiple projects in applications of machine learning and artificial intelligence into the ag domain. This area is developing rapidly and across UQ, I am engaging with faculty in multiple schools (ITEE, Maths and Physics, Mining and Mech Engineering) as well as in the Research Computing Centre to develop new projects and training opportunities at the interface of field agriculture and these new digital analytics.
• My career research has been around genetic and environment effects on physiology of field crops, particularly where drought dominates. Application of quantitative approaches (crop simulation and statistical methods) and phenotyping (aerial imaging, canopy monitoring) to integrate the understanding of interactions of genetics, growth and development and the bio-physical environment on crop yield. In recent years, this work has expanded more generally into various applications in digital agriculture from work on canopy temperature sensing for irrigation decisions (CSIRO Entrepreneurship Award 2022) through to applications of deep-learning to imagery to assist breeding programs.
• Much of this research was undertaken with CSIRO since 1996. Building on an almost continuous collaboration with UQ over that time, including as an Adjunct Professor to QAAFI, Prof Chapman was jointly appointed (50%) as a Professor in Crop Physiology in the UQ School of Agriculture and Food Sciences from 2017 to 2020, and at 100% with UQ from Sep 2020. He has led numerous research projects that impact local and global public and private breeding programs in wheat, sorghum, sunflower and sugarcane; led a national research program on research in ‘Climate-Ready Cereals’ in the early 2010s; and was one of the first researchers to deploy UAV technologies to monitor plant breeding programs. Current projects include a US DoE project with Purdue University, and multiple projects with CSIRO, U Adelaide, La Trobe, INRA (France) and U Tokyo. With > 8500 citations, Prof Chapman is currently in the top 1% of authors cited in the ESI fields of Plant and Animal Sciences and in Agricultural Sciences.

Jen Jen Chung is an Associate Professor in Mechatronics within the School of Information Technology and Electrical Engineering at The University of Queensland. Her current research interests include perception, planning and learning for robotic mobile manipulation, algorithms for robot navigation through human crowds, informative path planning and adaptive sampling. Prior to working at UQ, Jen Jen was a Senior Researcher in the Autonomous Systems Lab (ASL) at ETH Zürich from 2018-2022 and was a Postdoctoral Scholar at Oregon State University researching multiagent learning methods from 2014-2017. She completed her Ph.D. on information-based exploration-exploitation strategies for autonomous soaring platforms at the Australian Centre for Field Robotics in the University of Sydney. She received her Ph.D. (2014) and B.E. (2010) from the University of Sydney.

Shane Culpepper is Professor of Artificial Intelligence at the University of Queensland in St. Lucia, Australia. Before joining the University of Queensland in 2023, Professor Culpeper held a continuing academic position at RMIT University in Melbourne, Australia. He received his PhD in Computer Science from the University of Melbourn in 2008. His research focuses primarily on building better Search and Recommendation Systems. Over his 16 year career, Professor Culpepper has supervised 19 PhD students and co-authored more than 120 peer reviewed papers with 127 different research collaborators on problems such as algorithm efficiency and scalability, new machine learning algorithms for search and recommendation systems, and evaluating search and recommendation engine quality. Professor Culpepper is also an active member in the international research community. In the last 5 years, he has been a program co-chair for international conferences such as SIGIR and CIKM, and co-organized conferences such as WSDM and SWIRL. Professor Culpepper previously held an ARC DECRA fellowship in 2013 as well as an RMIT Vice-Chancellor's Princpal Researcher fellowship in 2017. Before joining the University of Queensland. Professor Culpepper was the founding director of the Centre for Information Discovery and Data Analytics at RMIT University. In total, he has been a chief investigator on 11 reseach grants totalling ~$3.5 Million AUD. For more information, see his personal hoomepage.

Pratap is an IP Strategist and Patent researcher. He has expertise in dealing with Intellectual Property issues in relation to emerging technologies such as Artificial Intelligence (AI), 3D bioprinting and synthetic biology. He is currently a Postdoctoral fellow at TC Bernie School of Law, University of Queensland, Australia. Pratap pursued his PhD from the Centre for Law and Genetics, University of Tasmania, Australia where his research was focused on "Patenting issues related to Bioprinted tissues and Bioinks." In 2018, he was invited by Govt. of Japan to assist the Japanese Patent Office (JPO) in harmonizing Japanese Patent Law in relation to AI. In 2017, he completed his Master of Law (LLM) in Intellectual Property from the World Intellectual Property Organization (WIPO), Geneva and the Queensland University of Technology, Australia. He is the recipient of the prestigious International Fellowship offered by WIPO. He holds a Master's degree in Genomics from the Central University of Kerala, India and a Bachelor’s degree in Biotechnology, Microbiology, and Chemistry from Acharya Nagarjuna University, India. Pratap also holds a Postgraduate Diploma in Patent informatics from the Academy of Scientific and Innovative Research (AcSIR) at the CSIR Unit of Research and Development of Information Products (URDIP), India and worked as a Patent researcher in the same.

Gordon holds a PhD in Chemical Engineering from the University of Cape Town, South Africa, which focused on the application of machine vision, image processing and machine learning algorithms for modelling grade in froth flotation systems.

Gordon spent ten years working for the Victorian Government developing technical computing and modelling solutions. These included the development of the Environmental Systems Modelling Platform, a tool that aims to bring multiple environmental models and datasets into a single easy to use software package, and the development of the Native Vegetation Regulations Tool, to calculate the interactions between proposed clearings and models of rare and threatened species, and thereby determine the required offset credits. More recently, Gordon worked as a data scientist at the Victorian Centre for Data Insights, where he worked with a team focused on delivering innovative data driven solutions across the government sector.

Gordon now applies his data analytics, modelling and technical computing skills at the JKMRC where he works with the Advanced Process Prediction and Control group developing tools for improved time series analysis and visualisation of industrial data and comminution process models.

Dr. Anthony Halog: A Pioneer in Sustainable Systems and Circular Economy

Dr. Anthony Halog is a leading authority in sustainable systems engineering and circular economy, with over 22 years of post-PhD experience in academia and research. His work focuses on integrating life cycle assessment (LCA), systems thinking, and industrial ecology to advance global sustainability efforts. Dr. Halog has successfully led numerous research projects in industrial ecology and sustainable supply chain management, contributing significantly to the United Nations Sustainable Development Goals (UNSDGs) and Planetary Boundaries frameworks.

His prolific career includes over 125 publications that have been widely cited and referenced in policy documents by international bodies such as the United Nations and the European Union. With a strong commitment to mentoring, Dr. Halog has guided numerous PhD candidates and postdoctoral researchers, fostering the next generation of sustainability experts. Since completing his PhD, he has examined numerous theses from various universities in Australia, North America, Africa, and Asia. His experience also extends to reviewing several grant proposals for prestigious funding bodies, including the National Science Foundation in the USA and European funding schemes.

Dr. Anthony Halog has received numerous fellowships and awards throughout his career. Notably, he was awarded fellowships from prestigious institutions such as the OECD, DAAD, and the Japan Society for the Promotion of Science (JSPS). He has held visiting fellowships across the globe, including in the UK, Germany, Japan, and Saudi Arabia, focusing on areas like Circular Economy, Green Hydrogen Policy, and Life Cycle Assessment. Dr. Halog's accolades also include early career fellowships from NSERC (Canada) and JSPS, along with several international research grants and academic scholarships, reflecting his global recognition in sustainability science and engineering.

Key areas of expertise include circular economy, bioeconomy, LCA, sustainable supply chain management, and the application of operations research and optimization in engineering sustainable systems. Dr. Halog’s interdisciplinary approach and international collaborations have positioned him as a thought leader in transitioning to a low-carbon, circular economy.

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.

Dr Leah Henrickson is a 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 ecosystems. Dr Henrickson also studies digital storytelling for critical self-reflection, community building, and commercial benefit. She regularly supports projects and organisations in their digital storytelling efforts as consultant and advisor.

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

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 (in the commonwealth system, is broadly equivalent to a North American full professor) (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 (6000+ citations, h-index: 40, i10-index: 111): https://scholar.google.com/citations?user=dIIYVQkAAAAJ&hl=en
• DBLP (170+ 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 techniques
• Moving Target Defense (MTD): Resilient and Proactive Defence
• Evolving Attacks and Defense Automation: Red team and Blue team Automation and evaluation using AI

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

• 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]
• 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. (US), NEC (Japan), Tait Comm. (NZ), MBIE (NZ), NPRP (Qatar), ADD (Republic of Korea), NRF (Republic of Korea), etc.

Recent Ph.D. graduates (selected)

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

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

3. 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).

4. 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).

5. 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).

6. 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 ).

7. 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. )

8. Mengmeng Ge (Ph.D., Computer Science, University of Canterbury, 2018; senior supervisor): Graphical security modeling and assessment for the Internet of things (Lecturer (continuing academic) in Cybersecurity at Deakin University -> RMIT University, Australia -> Deloitte New Zealand-> Senior Lecturer, University of Canterbury, New Zealand).

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

10. 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)

11. 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)

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 worked with diverse groups of people from various countries including Australia, Bangladesh, Brazil, China, Germany, 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).

Dr Jessica Korte is passionate about the ways good technology can improve lives. To ensure technology is “good”, she advocates involving end users in the design process; especially when those people belong to “difficult” user groups - which usually translates to “minority” user groups. Her philosophy for technology design (and life in general) is that the needs of people who are disempowered or disabled by society should be considered first; everyone else will then benefit from technology that maximises usability. Her research areas include Human-Computer Interaction, Machine Learning, and Participatory & Collaborative Design.

Jessica was drawn to research by a desire to explore some of the ways technology and design can empower and support people from marginalised groups. She has worked with Deaf children and members of the Deaf community to create a technology design approach, and successfully organised and run international workshops on Pushing the Boundaries of Participatory Design, leading to the World’s Most Inclusive Distributed Participatory Design Project.

Jessica has recently been awarded a TAS DCRC Fellowship to create an Auslan Communication Technologies Pipeline, a modular, AI-based Auslan-in, Auslan-out system capable of recognising, processing and producing Auslan signing.

Jessica is currently looking to recruit research students with an interest in exploring topics in an Auslan context, including machine learning, natural language processing, chatbots, video GAN, or procedural animation.

Dr Moni holds a PhD in Artificial Intelligence & Data Science in 2014 from the University of Cambridge, UK followed by postdoctoral training at the University of New South Wales, University of Sydney Vice-chancellor fellowship, and Senior Data Scientist at the University of Oxford. Dr Moni then joined UQ in 2021. He also worked as an assistant professor and lecturer in two universities (PUST and JKKNIU) from 2007 to 2011. He is an Artificial Intelligence, Computer Vision & Machine learning, Digital Health Data Science, Health Informatics and Bioinformatics researcher developing interpretable and clinical applicable machine learning and deep learning models to increase the performance and transparency of AI-based automated decision-making systems.

His research interests include quantifying and extracting actionable knowledge from data to solve real-world problems and giving humans explainable AI models through feature visualisation and attribution methods. He has applied these techniques to various multi-disciplinary applications such as medical imaging including stroke MRI/fMRI imaging, real-time cancer imaging. He led and managed significant research programs in developing machine-learning, deep-learning and translational data science models, and software tools to aid the diagnosis and prediction of disease outcomes, particularly for hard-to-manage complex and chronic diseases. His research interest also includes developing Data Science, machine learning and deep learning algorithms, models and software tools utilising different types of data, especially medical images, neuroimaging (MRI, fMRI, Ultrasound, X-Ray), EEG, ECG, Bioinformatics, and secondary usage of routinely collected data.

• I am currently recruiting graduate students. Check out Available Projects for details. Open to both Domestic and International students.

Javad Pool is a Postdoctoral Research Fellow at The University of Queensland. He completed his PhD in Business Information Systems at UQ Business School in 2022, with a focus on data privacy and the effective use of information systems, specifically in the digital health context. By employing a combination of qualitative and quantitative research methodologies, Javad has conducted studies in a wide range of organizational and technological contexts, including healthcare, artificial intelligence, digital health, and social media. His work includes the development of inductive and theory-driven models, contributing to the existing body of knowledge on the effective use of information systems and health informatics research. Passionate about collaboration, Javad seeks to engage with diverse stakeholders, encompassing multidisciplinary researchers, industry professionals, and government partners, to advance research on information resilience and data protection practices. His research endeavors to better understand and address socio-technical challenges within information systems use, including data governance, privacy risks, cybersecurity, data breaches, data protection, misinformation, and responsible use of data.

Research interest: Monitoring ecosystem health of coral reefs and seagrass habitats, integrating field and remote sensing image datasets, and the developing applied cost-effective mapping and monitoring approaches. Developed approaches have been adopted as standard practice globally, making a difference in conservation of these valuable habitats. The long term monitoring studies at Heron and Moreton Bay formed the basis for the development of mapping and monitoring over time and space at local to global scale.

Current projects:

1) Long term monitoring of benthic composition at Heron Reef (2002-ongoing). Annual photoquadrate surveys are being collected at Heron Reef, Southern Great Barrier Reef. Initiated to develop remote sensing mapping approaches and assess coral composition over time. The resulting Maps, photo quadrate and benthic data, spectral reflectance are accessible online.

2) Long term monitoring of seagrass composition and abundance in Moreton bay Marine Park (2000-ongoing). For Eastern Banks it included monitoring seagrass species, cover and biomass 15x times since 2004 using photoquadrate survey and satelite imagery and for Moreton Bay it included seagrass extent and cover (2004, 2009, 2015, 2021, 2022), all data accessible via Moreton Bay Research Station.

3) Smart Sat CRC Hyperspectral Remote Sensing of Seagrass and Coral Reefs 2023-2027. Collaborative effort with CSIRO, Adelaide University, DES Adelaide Coastal Waters.

4) 3D GBR Habitat Mapping Project 2015 - ongoing: Mapping and monitoring geomorphic zonation, bottom type and predicted coral type habitat for every Great Barrier Reef within the Marine Park.

5) Global habitat mapping project 2019-2023 Developed and implemention of global habitat mapping as part of the Allen Coral Atlas resulting in extent, geomorphic and benthic maps for reefs globally, funded through with Vulcan Philanthropies in partnership with; Planet; the Arizona State University and the National Geographic Society.

Other projects: Advisor for Reef Cloud Australian Institute of Marine Science and Coordinated Global Research Assessment of Seagrass System (C-GRASS).

Current position: Associate Professior in Marine Remote Sensing. Academic Director Heron Island Research Station and affiliated researchers with Centre for Marine Science and Centre for Biodiversity and Conservation Science

Capacity building: under/post graduate courses; Msc/PhD supervision, workshops/courses; Remote Sensing Educational Toolkit, and online courses (e.g. TNC)

Citizen science: Strong supporter of citizen science based projects, as trainer, organiser and advisor for Reef Check Australia, CoralWatch, Great Reef Census and UniDive.