I am the Director of the Environmental Informatics Hub at the Faculty of Information Technology, Monash University, and Professor of AI in the Department of Data Science and AI. My research lies at the forefront of linking domain sciences—such as ecology, epidemiology, and social sciences—with advanced quantitative tools from artificial intelligence (AI), developing innovative methods for smart decision-making under uncertainty and resource constraints. Building on my PhD work with Markov decision processes (MDP) applied to mobile robotics, I shifted my focus in 2006 to apply these principles in conservation science by integrating AI with ecological and economic models to solve complex applied problems.

International leader of interdisciplinary research integrating AI and decision science with conservation, ecology, epidemiology and social sciences addressing critical environmental and societal challenges:

• Inclusive interdisciplinary leader on AI for environmental and societal good: extensive experience in leading interdisciplinary research on AI for environmental and societal good, biodiversity conservation and epidemiology. Highly experienced in bringing together large and small integrated multi-disciplinary teams including data scientists, economists, social scientists, ecologists, applied mathematicians, and engineers, to address complex foundational and applied problems involving stakeholders to achieve on ground impact. 
• Pioneered the development of AI for nature with major research contributions including: discovery of key mechanistic insights to manage and survey endangered species, invasive species and diseases (e.g., 2 PNAS papers, lead author); novel algorithms to optimally guide the implementation of adaptive management programs and experimental designs (e.g., AAAI’12 best paper award, lead author); new models to increase interpretation of AI models and solutions (e.g., K-MDP, K-N-MOMDP, last author) to increase uptake by stakeholders.
• Achieved significant impacts on policy and implementation through delivery of key strategic decision tools to inform conservation investment in Australia (e.g. Pilbara, Lake Eyre Basin, NSW state, and QLD state) and internationally (e.g. Canada, Antarctica). For example, these tools inform the investment of $160M towards NSW listed species (Saving our Species program) and $60M/year towards conservation activities on private lands (NSW Biodiversity Conservation Trust).

• AI for the environment
• Decision science
• Markov decision models
• Adaptive management
• Value of information
• XAI and interpretability
• Conservation of biodiversity
• Epidemiology
• Responsible AI

I am seeking passionate PhD candidates with a strong background in mathematics and computer science who are interested in artificial intelligence for environmental applications, particularly biodiversity conservation. 

Please apply directly using supervisor connect:

• PhD project : Adaptive sequential decisions to maximise information gain and biodiversity outcomes
• Masters / Honours: Don’t Miss the Exit: Identifying Critical States in Sequential Decision-Making for Biodiversity

My current and recent supervision includes:

• Dr Martin Cyster (Research Fellow, University of Melbourne)
• Dr Dominik Behr (Research Fellow, Faculty of IT, Monash University)
• Dr Haoran Li (Research Fellow, Faculty of IT, Monash University)
• Dr Frankie Cho (Research Fellow, Faculty of IT, Monash University)
• Luz Valerie Pascal (PhD Candidate, QUT)
• DangFeng Pan (PhD Candidate, Faculty of IT, Monash University)