Maia Watson-Hearne
Imperial| Imperial | |
| London, United Kingdom | |
| Member ID | 5309 |
|---|---|
| Member since | Mar 14, 2026 |
| Status | Active |
Sections
About
I am a PhD researcher in Civil and Environmental Engineering at Imperial College London working on quantitative modelling of global food systems. My research focuses on applying industrial ecology methods to biological systems in order to better understand the resource dynamics and environmental implications of food production, processing, consumption, and waste.My doctoral work develops a Bayesian material flow analysis (BaMFA) framework for modelling resource stocks and flows across the global food system. By integrating probabilistic modelling with material flow analysis, the work introduces uncertainty-aware approaches to analysing complex biological production systems. This allows the food system to be examined as a socio-ecological metabolism, enabling comparison between existing production structures and alternative configurations.
Within industrial ecology, my interests focus on extending systems-based analytical tools—particularly material flow analysis—to emerging food system challenges. I am particularly interested in questions relating to food system metabolism, resource efficiency, circular economy strategies in agri-food systems, and the environmental and socioeconomic implications of transitions toward alternative protein sources such as plant-based and cultivated meat.
More broadly, I am interested in how industrial ecology frameworks can contribute to the redesign of food systems so that they operate within planetary boundaries while remaining resilient, equitable, and resource-efficient.
Details
I am a PhD researcher in the Department of Civil and Environmental Engineering at Imperial College London. My doctoral research applies Bayesian material flow analysis (BaMFA) to quantify resource stocks and flows across global food systems, representing the first application of this methodology to biological systems. The work builds on a probabilistic, uncertainty-aware model of the food system, from agricultural production through processing, distribution, consumption, and waste management, enabling comparison of the status quo against alternative food system configurations.The increasing pressures of global population growth and urbanisation are intensifying demand for food while driving land use change, with agricultural activity now a leading driver of climate change, biodiversity loss, and disrupted nutrient cycles, several of which are exceeding recognised planetary boundaries. My research aims to address a critical gap in understanding the socioeconomic and environmental trade-offs associated with emerging food products, such as plant-based proteins and cultivated meat, and novel system-level arrangements of production, use, and waste management activities.
Within the field of industrial ecology, my work contributes to the growing interest in analysing food systems as complex socio-ecological metabolisms. By integrating probabilistic modelling with material flow analysis, the research introduces a framework that explicitly accounts for uncertainty in data, parameters, and system relationships. This allows the model to identify critical knowledge gaps while providing more robust estimates of resource flows and environmental pressures across the food system.
Substantively, my research examines how transitions in production technologies and consumption patterns may reshape the material and energy metabolism of food systems. I am particularly interested in the environmental and resource implications of alternative protein systems, including plant-based and cultivated meat, as well as the potential role of circular economy strategies such as the recovery and reuse of agricultural residues, food processing by-products, and organic waste streams.
More broadly, my work seeks to explore how industrial ecology frameworks can support the redesign of food systems so that they operate within planetary boundaries while remaining resilient, equitable, and adaptable to diverse social and economic contexts. By combining systems modelling with uncertainty-aware analysis, I aim to generate insights that can inform both policy discussions and emerging technological pathways for sustainable food system transformation.
Prior to joining Imperial, I studied Geography with Social Data Science at University College London, where my undergraduate dissertation on food security was awarded the Q-Step Best Dissertation Prize and the Royal Geographical Society Quantitative Methods Research Group Dissertation Prize.
Research Interests
My research interests sit at the intersection of quantitative environmental modelling and food systems sustainability. Methodologically, I am interested in Bayesian and probabilistic approaches to material flow analysis, particularly in how uncertainty quantification can surface data gaps and improve the rigour of systems-level environmental assessment. Substantively, I am drawn to questions of food security and resource efficiency across the global food system, including the role of circular economy strategies, such as the recovery and reuse of food processing by-products, crop residues, and organic waste streams, in reducing systemic resource losses.I am equally interested in the transition from conventional to alternative food systems and sources, including the shift toward plant-based proteins, cultivated meat, and novel system-level arrangements of production, distribution, and consumption, and in how the socioeconomic and environmental trade-offs of these transitions can be characterised relative to the status quo. Cutting across both, I am interested in how food systems can be redesigned to operate within planetary boundaries, with respect to climate, biodiversity, and nutrient cycles, while remaining equitable, resilient, and appropriate to diverse social and economic contexts. Finally, I have particular interested in how quantitative modelling can generate actionable insight for policy, moving beyond high-level sustainability narratives to interrogate the real trade-offs involved in transitioning toward alternative food products and system configurations.