Associate ProfessorRobert Faggian

Robert's research examines how institutions make consequential decisions about climate risk, land, water, agriculture and regional development, and how models, data and AI-enabled tools are used, and sometimes misused, to inform those decisions. This work sits within the Climate Governance and Decision Systems programme, which he convenes across research in Latin America, India and Europe, with linked work in Australia.

A first strand addresses climate change impacts, risk and vulnerability across urban, peri-urban and regional systems, including impacts on land use, water systems, agriculture, food security and human health in vulnerable communities. The emphasis is on how climate-risk information is translated into planning and policy decisions, not on impact assessment as an end in itself.

A second strand addresses adaptation pathways, governance and implementation: what makes adaptation strategies feasible, legitimate and defensible in practice. This includes nature-based solutions and blue-green infrastructure, agricultural adaptation under climate and market uncertainty, and the institutional design and policy frameworks that shape adaptation outcomes. The work treats adaptation as a matter of trade-offs and institutional constraint, rather than a technical optimisation problem with a single correct answer.

A third strand examines decision-support tools themselves: spatial analysis, multi-criteria assessment, scenario modelling under deep uncertainty, and AI-enabled or agent-based approaches. This work asks when these tools are informative, when they are misleading, and when they should not be used to justify a decision at all. Questions of transparency, legitimacy and accountability run through this research, since these tools are often used to support decisions with long-term, path-dependent or difficult-to-reverse consequences.

Robert welcomes enquiries from students, collaborators and partner organisations working on any of these strands, particularly where the goal is to make analysis usable by, and accountable to, the institutions expected to act on it.