Biography
Patrick Thomson is Technical Manager and Senior Research Associate at the IBME’s Computational Health Informatics Lab. He supports the Computational Health Informatics (CHI) Lab, led by Professor David Clifton, which focuses on AI for Healthcare.
Patrick is also a Senior Research Associate at the Oxford University’s School of Geography and the Environment, and a member of the Social Sciences & Humanities Interdivisional Research Ethics Committee. Prior to returning to Oxford in 2010, Patrick worked in international development, living and working in Sub-Saharan Africa, Southeast Asia and the Caucasus regions. He is a Chartered Engineer and has been granted three patents.
Most Recent Publications
Water supply interruptions are associated with more frequent stressful behaviors and emotions but mitigated by predictability: a multisite study
Water supply interruptions are associated with more frequent stressful behaviors and emotions but mitigated by predictability: a multisite study
The impact of rapid handpump repairs on diarrhea morbidity in children: cross-sectional study in Kwale County, Kenya
The impact of rapid handpump repairs on diarrhea morbidity in children: cross-sectional study in Kwale County, Kenya
The challenges of implementing modular, adaptive, and decentralised water technologies – the perspective of a rural service provider in Kenya
The challenges of implementing modular, adaptive, and decentralised water technologies – the perspective of a rural service provider in Kenya
MAD water: integrating modular, adaptive, and decentralized approaches for water security in the climate change era
MAD water: integrating modular, adaptive, and decentralized approaches for water security in the climate change era
Incentivizing clean water collection during rainfall to reduce disease in rural sub-Saharan Africa with weather dependent pricing
Incentivizing clean water collection during rainfall to reduce disease in rural sub-Saharan Africa with weather dependent pricing
Research Interests
Patrick’s research focuses on how information enables household and institutions to rethink and redesign rural water services to improve human development outcomes. This praxis-based research mixes social science, natural science and engineering. This work includes operationalising novel technologies and management models, including researching how AI techniques and methods can be applied to data sparse rural contexts.
Research Groups
Related Academics
Most Recent Publications
Water supply interruptions are associated with more frequent stressful behaviors and emotions but mitigated by predictability: a multisite study
Water supply interruptions are associated with more frequent stressful behaviors and emotions but mitigated by predictability: a multisite study
The impact of rapid handpump repairs on diarrhea morbidity in children: cross-sectional study in Kwale County, Kenya
The impact of rapid handpump repairs on diarrhea morbidity in children: cross-sectional study in Kwale County, Kenya
The challenges of implementing modular, adaptive, and decentralised water technologies – the perspective of a rural service provider in Kenya
The challenges of implementing modular, adaptive, and decentralised water technologies – the perspective of a rural service provider in Kenya
MAD water: integrating modular, adaptive, and decentralized approaches for water security in the climate change era
MAD water: integrating modular, adaptive, and decentralized approaches for water security in the climate change era
Incentivizing clean water collection during rainfall to reduce disease in rural sub-Saharan Africa with weather dependent pricing
Incentivizing clean water collection during rainfall to reduce disease in rural sub-Saharan Africa with weather dependent pricing
