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Helen's research interests cover biodiversity conservation and human health, and how decisions in these fields could be optimised to achieve mutual gains for people and the environment. Her underlying goal is to facilitate evidence-based decisions in these fields by making data modelling and decision science more accessible to decision makers, regardless of the quality or nature of their data. Her interest in BNs therefore includes using them both as a machine learning technique and as a participatory modelling tool.

Yue is a lecturer at the Sydney School of Public Health, the University of Sydney. Yue was trained in mathematical biology with her PhD research focusing on the theoretical evolution of bacterial genomes and its implications in the antimicrobial resistance problem. With growing interest in health and clinical research, Yue's current research interests lie in the development of clinical decision support tools for managing patients presenting to healthcare for infectious diseases, using Bayesian network models. This involves closely working with medical experts to create models that describe the causal pathophysiological and clinical processes underlying the clinical manifestation of disease. She has participated and led projects on the diagnosis and prognosis of serious infections in children, as well as COVID-19.

Shannon is a statistical modeller at GNS Science in Wellington, New Zealand. His research focuses on coastal hazard modelling for Pacific communities, aiming to equip policy makers with vital information in our changing climate. With a background in data science, he has a keen interest in applying machine learning techniques to environmental datasets. Shannon is the team leader of the Earthquake Physics and Statistics team at GNS Science. Shannon has a background in engineering and a PhD in paleoceanography from The University of New South Wales.

Dr Annemarie Christophersen is a senior scientist at GNS Science, New Zealand. Annemarie first came across Bayesian networks in the context of developing risk assessment method for carbon capture and storage and has since worked with colleagues in volcanology on models for eruption forecasting and with colleagues in climate modelling on Antarctic ice-sheet stability. Annemarie has been on the board of ABNMS since 2016 and was the president in 2019.

Bruce Marcot, Ph.D., is a Research Wildlife Biologist with the Ecosystem Process and Function Research Program of U.S. Forest Service in Portland, Oregon, USA. He participates in applied science research and technology application projects dealing with old-forest management, analysis of rare and little-known species, assessment of biodiversity, and ecological research in regions from the arctic to the tropics. He has provided advances in integrating Bayesian network modelling with decision science, expert elicitation, rare event statistics, and environmental monitoring.

Anca is a senior research fellow based at the Centre of Excellence for Biosecurity Risk Analysis (CEBRA) at the University of Melbourne. She is a research associate at the Centre for Environmental and Economic Research (CEER) and at the Interdisciplinary MetaResearch Group. Her research interests and experience lie in high dimensional dependence modelling, risk analysis, decision theory, probabilistic graphical models, and structured expert judgement.

Trent is a bushfire risk modeller interested in all aspects of bushfire management. His work covers a range of theoretical and applied aspects of bushfire behaviour and management. The main focus of his research is optimising management expenditure to reduce the risk of detrimental fire impacts on people, property and the environment. Over the last ten years, his research has combined fire simulation with risk research methodologies such as Bayesian Networks. Trent teaches undergraduate and masters level subjects and supervises a range of research students from laboratory studies of fire fundamentals, field based research projects on fire and fire ecology and computer based studies including remote sensing, fire behaviour simulation and species distribution modelling.

Andrew is currently Group Leader of Red Teaming and Wargaming within the Joint Operations Analysis Division in the Defence Science and Technology Group. He has recently completed 40 years working for Defence in diverse roles ranging from soldier/technician, communications engineer and finally as an operations analyst. In recent years Andrew completed a PhD through the University of New South Wales that applied a Bayesian Network approach to support Political-Strategic crisis decision making. Andrew has been on the board of ABNMS since 2016.

Kate is research fellow at the University of Melbourne in the Bushfire Behaviour and Management Team. Kate is currently undertaking post-doctoral research as a bushfire risk analyst. Her current research interests include fire risk modelling, particularly the integration of cultural and environmental assets into risk planning, fire management and forest ecology. Kate is particularly interested in Bayesian Network Modelling for the integration of multiple data sources, spatialisation of risk, and as a decision-support tool. Kate completed her PhD in fire ecology at the University of Melbourne in 2018. Her research focused on how fire affects ecological processes in flammable systems, with a focus on fire-induced edge effects and the implications for native fauna. Her previous research had a focus on large forest owls, threatened species conservation and species distribution modelling. Kate also has a Bachelor of Arts/Communications degree and is passionate about science communication.

Dr Owen Woodberry is a Director and Senior Consultant at Bayesian Intelligence. He has worked in Bayesian networks since 2003, where he worked on the development of a model of native fish populations in the Goulburn Broken Catchment in Victoria. Since then, he has worked on the development of a wide range of BN models, including in domains such as ecology, health, infectious diseases, fire, biosecurity and asset management. He has interests in the knowledge engineering of BNs, machine learning, software development and teaching.

Dr Steven Mascaro is a Director and Senior Consultant at Bayesian Intelligence. He began working with BNs in 2006, contributing to the development of Monash University's BN-based poker playing bot. Since then, he has worked on development of models and software, both elicited and machine learned, in domains including ecology, defence, biosecurity, fire, children's health and infectious diseases and rail maintenance. His main interests are in machine learning and causal discovery, as well as in expert elicitation and, in particular, software and techniques for structuring and automating the elicitation process.