Dr Mel McDowall, Director of DAIRNet
Bio: Dr Mel McDowall is the Director of the Defence AI Research Network (DAIRNet), an initiative of the Department of Defence and hosted by the University of South Australia. This draws on her experiences in transdisciplinary research and operation roles.
Having worked in many industries, such as clinical, agriculture and Defence, Mel has experience with many steps in the ""bench to bedside/farm-gate/capability"" journey. This includes basic and applied research, business improvement and governance, advocacy, contract management, territory management, and clinical support. Transdisciplinary teams, science communication and outreach are critical for research. Highlights of Mel’s career include receiving a Young Tall Poppy Award (2005), attending Science Meets Parliament (2014-2016) as an advocate for reproductive medicine research, and participating in the CSIRO Nonprime program (2016). More recently Mel was the 2023 winner of the Technology category of the Women in Technology awards and a finalist in the Defence Connect “Women in Leadership” award (2023).
Mel holds a PhD in Medicine (2005) and Master of Business Administration (2018) from the University of Adelaide.

Dr Truyen Tran, Head of AI, Health and Science, Applied Artificial Intelligence Institute (A212), Deakin University
Title: Neural memory architectures for scalable reasoning over temporal multimodal data.
Abstract: Multimodal data - like text, audio, video, and sensor feeds - offer powerful insights but are challenging to analyse effectively. This challenge is particularly acute when working with data from multiple sensors and network systems that generate vast amounts of information over time. Despite these challenges, such data analysis can deliver significant benefits. For example, it can enhance cyber threat detection, enable real-time situational awareness, and support intelligent decision-making by analysing network patterns and system behaviours. To address these challenges, we present UNITED - a scalable AI framework that integrates self-supervised learning with deep reasoning capabilities. UNITED is designed to process complex, time-varying data from multiple sources using advanced encoding techniques and memory systems. This enables accurate analysis and prediction across extended timeframes. UNITED implements three specialised architectures: 1) A system which organises information in a variable-size hierarchical memory; 2) A system featuring a controlled memory module for complex reasoning tasks, and 3) A system which uses multiple specialised memory modules for handling diverse data types. This general framework advances our ability to process complex multimodal data for real-world applications across Defence, industry, and research domains.

Bio: Dr. Truyen Tran is a Full Professor at Deakin University, Australia, where he leads a world-class team developing robust human-compatible Artificial General Intelligence (AI Future).
This technology is then leveraged to accelerate science and engineering (AI4Science) and improve health outcomes (AI4Health). AI Future envisions AI agents as a new digital species integrated into our society, equipped with advanced reasoning and planning capabilities while maintaining robust alignment with human values. His AI4Science research program develops AI Scientists spanning all STEM fields, while the AI4Health program focuses on clinical prediction, medical image analysis, and Generative AI for healthcare.
Dr. Tran has received multiple international awards for his significant research contributions. He obtained his BSc degree from the University of Melbourne in 2001 and a PhD in Computer Science from Curtin University in 2008.

Dr Kobi Leins, Consultant, Info Sphere Education, helping with your AI and data innovation journey
Title: The Standard of Article 36 reviews: Connecting military and civilian AI governance.
Abstract: Before any means or method of warfare is deployed in armed conflict, the legality of its use should be confirmed by legal review, at the stage of “study, development, acquisition or adoption.” This review should ensure that new means and methods of warfare comply with international law. International law is comprised of treaties, international custom, and general principles of law.
This legal review ensures that all new or modified means or methods of warfare comply with general legal principles, for example, the requirement that they are not “of a nature to cause superfluous injury.” Examples of treaty-based obligations include prohibitions on poisons, or biological or chemical weapons, just to name a few.
“Nano” is a prefix meaning “a billionth” (a factor of 10−9 of a meter) derived from the Greek νᾶνος, meaning, “dwarf”. By way of illustration, a nano-sized object is to an apple, what an apple is to the size of the earth. Or to give another example, one nanometer particle could fit approximately 80 000 time across a human hair.
Bio: Dr Kobi Leins (GAICD) is a global expert in AI, international law and governance with expertise spanning academia, corporate and global enterprises.
Leins provides strategic advice on selection, implementation and operation of technologies to drive business edge; creates systems for organisational and delegation of ownership for complex systems and data; and uses international benchmarking to analyse opportunities and risks in face of rapidly changing legal and governance landscapes and data literacy and public sentiment.
Leins is a Member of Standards Australia as a technical expert on the International Standards Organisation’s work on AI Standards; Affiliate, ARC Centre of Excellence for Automated Decision-Making and Society; and former Honorary Senior Fellow of King’s College, London; Advisory Board Member of the Carnegie AI and Equality Initiative; and Non-Resident Fellow of the United Nations Institute for Disarmament Research.
Leins is owned by 2 rescue dachshunds, supports two incredible teenagers, and sails on the bay in Melbourne for fun. Leins is the author of New War Technologies and International Law: The Legal Limits to Weaponising Nanomaterials, Cambridge University Press (2022).
Further publications by Leins and reading on this topic can be found at kobileins.com.

Dr Liming Zhu, Research Director, CSIRO's DATA61
Title: GenAI for Defence: From Cybersecurity to Enhanced Decision-Making.
Abstract: This talk will explore the application of GenAI within potential defence contexts ranging from cybersecurity to decision-making. It will cover how LLMs can be utilised to bolster cybersecurity across a variety of threat scenarios, including software supply chains. Moving beyond cybersecurity, the talk will introduce reference designs for improving decision-making capabilities through the integration of third-party LLMs. Key focuses include scaffolding architectures, guardrails, design options, and the development of use case-specific learning structures that operate outside the model. By harnessing these elements, the talk aims to demonstrate how adaptable and secure, GenAI-driven systems can be tailored to meet the unique challenges of defence operations.
Bio: Dr Liming Zhu is a Research Director at CSIRO's Data61, the AI/digital arm of Australia's national science agency, and a conjoint professor at UNSW. He contributes to the OECD.AI’s AI Risks and Accountability, the Responsible AI at Scale think tank at Australia's National AI Centre, ISO AI standards committees, and Australia's AI safety standard. His research division innovates in AI engineering, responsible/safe AI, blockchain, quantum software, privacy, and cybersecurity, and hosted Australia's Consumer Data Right/Open Banking standards setting.
Dr Zhu has authored over 300 papers and is a regular keynote speaker. He delivered the keynote "Software Engineering as the Linchpin of Responsible AI" at the International Conference on Software Engineering. His latest book, "Responsible AI: Best Practices for Creating Trustworthy AI Systems" and "Engineering AI Systems: Architecture and DevOps Essentials," reflect his vision for the rigorous engineering of responsible and safe AI systems for society.
Personal Website: https://liming-zhu.org/.

Professor Hanna Kurniawati, SmartSat CRC Chair in System Autonomy, Intelligence and Decision Making, Australian National University
Title: Sequential Decision-making for Robots Operating in Non-Deterministic and Partially Observable Worlds
Abstract: In recent years, robotics hardware has advanced tremendously, with increasingly affordable humanoids, quadrupeds, telepresence robots, and many more. Despite these advances, developing autonomous or semi-autonomous robots that can reliably, efficiently, and safely operate in our environments remains an open problem. Key to this difficulty is the ubiquity of uncertainty. These robots must compute strategies to achieve their goals even when the outcomes of their actions are uncertain, their sensors and perception systems are erroneous, and the environments they operate in are dynamic and only partially observable. Moreover, they must ensure safety for both the robots and the humans around them. However, the technology that enables robots to efficiently construct effective strategies in the presence of a wide variety of uncertainty is still lacking. In this talk, I will present some of our work in developing such a technology, specifically in our work on the Partially Observable Markov Decision Processes (POMDPs) —the general and principled framework for sequential decision-making under uncertainty. I will also present how this technology can be applied for safety assurance of autonomous systems.
Bio: Hanna Kurniawati is a Professor in the ANU School of Computing and holds the SmartSat CRC Professorial Chair for System Autonomy, Intelligence & Decision-Making.
Hanna’s research spans robotics, sequential decision-making (planning) under uncertainty, motion planning, computational geometry applications, integrated planning and learning, and reinforcement learning. Hanna’s works have received multiple awards, including the Robotics: Science and Systems 2021 Test of Time Award. She is a Senior Editor of IEEE TRO, was a Senior Editor of IEEE RAL for Planning and Simulation area and a PC Co-chair for ICRA’22.

Dr Zygmunt Szpak, Executive Director, Insight Via Artificial Intelligence (IVAI) Pty Ltd
Title: From Noisy Data to Early Detection: Preliminary Insights and Challenges in Analysing Wearable Biosensor Signals from a Time-Locked Immune Challenge Study
Abstract: To explore the potential of consumer wearables for early infection detection, we conducted a unique, time-locked immune response study involving over 100 participants. Each participant was monitored using wearable biosensors that tracked signals such as heart rate variability, temperature, and respiratory rate, alongside daily questionnaire responses. Baseline data were collected over a ten-day period, followed by a vaccination, with monitoring continued for an additional three days to identify potential physiological markers of immune activation.
This talk will discuss the distinct challenges involved in analysing biosensor signals from wearables, including data variability, input errors, and the complexities of data cleaning and processing. We will present preliminary findings from our ongoing analysis. Additionally, we will outline our plans to refine these analyses, address data quality issues, and develop methodologies to more accurately identify reliable early indicators of immune response from wearable data.
By sharing both our findings and challenges, we aim to enhance the understanding of wearable-based health monitoring and examine its potential for real-time infection detection.
Bio: Dr Zygmunt Szpak is a Director of Insight Via Artificial Intelligence (IVAI) Pty Ltd, a technology company conducting research and product development in diverse Defence fields such as ISR, EW, IW, C2, Cyber and related areas. The company specialises in Artificial Intelligence, Machine Learning, and associated technologies such as Computer Vision, Natural Language Processing and Augmented Reality. IVAI has a strong focus on advancing human-machine teaming with trusted AI.

Dr Dale A. Lambert, FTSE
Bio: Dale A. Lambert has assumed a number of roles within Defence Science and Technology in the Australian Department of Defence, including Chief of Information Sciences Division; Chief of Cyber and Electronic Warfare Division; Chief of National Security and Intelligence, Surveillance and Reconnaissance Division; Director General of Science Strategy and Policy; and Research Leader of Intelligence Analytics.
Early in his career, Dale was contracted from Australian Defence to Swedish industry for four years to design and implement an Artificial Intelligence system for Sweden’s airborne defence. The final Swedish system was subsequently on-sold to several nations in Europe, Asia, and South America. Later in his career, Dale served as Chair of the Executive Chairs of the largest cooperation on defence science and technology between Australia, Canada, New Zealand, the United Kingdom, and the United States. In this role he provided administrative oversight of all sanctioned science and technology programs across these five nations, covering everything from aerospace systems to human performance.
A five nation Achievement Award was bestowed on Dale in 2006 with a Distinguished Service Award following in 2021. The Institute of Electrical and Electronics Engineers (IEEE) jointly presented Dale with the IEEE Harry Rowe Mimno Award at a ceremony in Washington DC in 2015 for “excellence in technical communication”. He was awarded the Public Service Medal in the 2020 Australia Day Honours for “outstanding public service in the use of artificial intelligence in surveillance and reconnaissance, command and control, intelligence and autonomous platforms”. In 2021 he was elected as a Fellow of the Australian Academy of Technological Sciences and Engineering.
Dale has been a member of multiple senior Defence committees, numerous university boards, and served as an international journal and conference reviewer on many occasions. He holds: a Bachelor of Science degree in Computer Science; a first-class Bachelor of Arts Honours degree covering both Philosophy from Humanities and Artificial Intelligence from Computer Science; a Bachelor of Arts degree in Mathematics; a Doctor of Philosophy doctoral degree in Artificial Intelligence; a Graduate Certificate of Management in Scientific Leadership; and the university’s rare highest degree, a Doctor of Science doctoral degree relating to Artificial Intelligence and Information Fusion.

Dr Ralph Gailis, Specialist Science Advisor, Artificial Intelligence, Defence Science and Technology Group (DSTG)
Bio: Ralph Gailis received his BSc (Hon) in physics and mathematics at the University of Melbourne in 1992. He completed his PhD in theoretical physics at the University of Melbourne in 1996, as well as a postdoc in 1997-1999, in the area of cosmology.
Ralph began working in Defence Science and Technology in 1999, contributing to a broad range of research topics including Chemical, Biological and Radiological (CBR) hazard modelling / threat analysis, diseases surveillance and epidemic modelling, and further work in data fusion and machine learning.
Ralph’s leadership roles have included leading a research group on CBR hazard analysis from 2007-2014, Scientific Adviser Army 2015-2017, and more recently various roles in Intelligence Analytics, Joint Force Experimentation and now the Deputy Program Leader for Artificial Intelligence.

Professor Jennifer Palmer, Head, Aerospace Engineering, School of Engineering, GAICD, RMIT University
Bio: As Head of the Department of Aerospace Engineering at RMIT University (Australia’s leading Aerospace department), Professor Jennifer Palmer leads a team of 25 staff and 85 research students specialising in aerospace engineering and aviation. Her current research is focussed on aerial autonomous systems, particularly teaming and swarming operations, along with the design and trialling of novel air vehicles. Jennifer has more than 20 years’ experience in industry, government, and academia and was previously Technology Program Director at the Trusted Autonomous Systems CRC.
Jennifer’s background includes a PhD on combusting supersonic/hypersonic flows at Stanford University; and she spent 15 years at the Australian Defence Science and Technology Group, where her focus was on hybrid power for small uncrewed aircraft, flapping flight, and autonomous systems for complex and contested urban environments, along with defence-oriented innovation. She is also a graduate of the Australian Institute of Company Directors.