| Benjamin Bach |
data visualization
data science
public engagement
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Working on data visualization and making data accessible and understandable by experts and non-experts. Data visualization is essential in understanding complex processes and data sets. Especially, techniques from storytelling and visual communication have huge potential to communicate findings and information to large and diverse audiences.
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climate smart technologies
agritechnology
environmental change
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| Development of mitigation strategies for greenhouse gas emissions from agri-environment systems. This includes international partnerships, and with non-academic stakeholders, to enhance a circular nutrient economy that lowers reliance on inorganic fertilisers in smallholder farming systems. |
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fintech
credit risk
climate change
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| Focus on incorporating climate change in the risk assessment process of financial institutions. Working with several Fintech companies in designing new services for financially vulnerable individuals. Also supporting small businesses in improving their chance of accessing external finance. |
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green washing
policy making
abuses of power
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| Interested in accounting technologies and how these strongly impact upon the majority of decisions made in organisations and government. |
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tropical livestock
genetic improvement
smallholder farmers
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pastoral livelihoods
livestock systems
climate uncertainty
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| Leads the Jameel Observatory for Food Security Early Action for University of Edinburgh. The Observatory is focused use of early warning technologies to better prepare for drought in East Africa. It's goals are to enhance wellbeing and reduce hunger among East African pastoral communities. |
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data & AI for good
climate change
responsible innovation
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| Research related to the future of work and HR. How organizations and HR department can empower innovation with the right diversity & inclusion, new edge leadership and inspiring culture within workforces. Understand the way in which HR can support ecosystems that consist of more community-driven learning and enforcing social capital along with human capital. |
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data & AI for good
climate change
responsible innovation
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The Data for Children Collaborative with UNICEF is a joint partnership between UNICEF, The Scottish Government and the University of Edinburgh’s Data Driven Innovation Programme which seeks to enable improvement in outcomes for every child. We draw on the strengths of our partners and their network to bring insight and solve problems using data and responsible innovative data practices, with a focus on delivering against the Sustainable Development Goals. Our mission is to provide the platform that brings together the appropriate data and expertise to answer our challenge questions for children across a variety of themes and geographies. |
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sustainable Food systems
agritech
animal welfare science
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| Interested in Sustainable Food Systems, and in particular the role of animal welfare science to ensure sustainable and socially acceptable food production systems. Leads the delivery of UG programmes and courses in Global Agriculture and Food Security, as well as the DDI Agritech Talent programme aimed at upskilling learners in data science and technology relevant to sustainable food systems. |
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renewable energy
technological solutions to manage the nexus between climate change and poverty
social science and policy
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| Interested in how policymakers and firms manage competing demands (e.g. economic vs. environmental goals) in the process of developing and providing technological solutions in response to societal challenges. |
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| John McCloskey |
risk
co-production
urbanisation
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We run the GCRF Tomorrow's Cities Hub which aims to reduce disaster risk for the 2 billion new urban residents of tomorrow's rapidly expanding cities. We use interdisciplinary methods to understand risk and tools for risk assessment that can democratise the concept of risk and allow poor communities to argue for safer and more human future urban expansion. |
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| environmental, agricultural and food systems economics |
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| Interested in definitions and metrics of sustainability, economic appraisal of technological options using non-market valuation, and behavioral and political appraisal of technology adoption. |
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| digital health and agrictech |
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| Develop tools to support Agriculture and Public health in LMICs |
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| one health, modelling, social sciences & policy |
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| Modelling antimicrobial use and resistance at the livestock-human interface in LMICs, with the aim of contributing to policy guidance for increased food security and health of livestock-keepers in LMICs as well as long-term global sustainability of antimicrobial drugs. |
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AI for social good
AI for health
AI for science
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| Interested in developing sustainable and explainable AI models from earth observation and household surveys to understand population, poverty, etc., and working with humanitarian organisations to make these tools accessible and operational. We also support data science activities throughout the University through consultancy, analysis and engagement. |
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life science innovation
policy and regulation
responsible innovation
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| Focus on genetic technology solutions to challenges relevant to Net Zero and biodiversity policy objectives, considering: development of business models and value chains for innovative technologies; regulatory systems, standards and guidelines and how they can support of constrain innovation. |
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| John Vines |
design
co-creation
data-driven technology
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Interested in issues of social responsibility around technology design and development, and co-creation of new systems with communities that are affected by and responsible for them. Conducted research around digital technologies and data-driven systems in relation to civic action, community development, and in general the role of technologies in supporting sustainable communities and address issues of social inequality. |
| Gary Watmough |
EO4SDGS
poverty mapping
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Interested in how satellite data can be leveraged for monitoring poverty and livelihoods. This is because we need more data on how SDGs are progressing but the traditional ways of doing this using household surveys are time consuming and expensive. |
