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Machine learning Intelligence Network for Epidemics (MINE) brings together a team of multidisciplinary researchers and experts from the UK and India to develop new methods and approaches for understanding, predicting and mitigating epidemics  using state-of-the-art machine learning and artificial intelligence. The team will look at epidemic impacts in the transdisciplinary domains of built-environment, energy, society and urban health. 

The project will use multi-modal data including demographics, geo-spatial, weather pattern, built environment and molecular level data for devising strategies for long term disease risk reduction. The methods will be developed through a workshop  which is aimed at building capabilities of early career researchers to acquire interdisciplinary perspectives, knowledge and skills needed for epidemics research. This workshop  will address the challenges of epidemics with specific reference to the promotion of health of socio-economically deprived groups. The consortia will also contribute to the development of a Master’s level course curriculum to build future capacities in strengthening urban health in the Global South. 

The details of the workshop and call for participants will be shortly announced!


Principal Investigators: Dr Ronita Bardhan, UK; Dr Jacquleen Joseph, India


Institution Network: University of Cambridge, UK, University of Oxford, UK, Tata Institute of Social Sciences, India, Indian Institute of Technology Bombay, India, Haystacks Analytics Pvt. Ltd, Mumbai, India


Funding Partner: This work was supported by Newton Fund Researcher Link Workshop, under the Newton-Bhabha Fund partnership. The grant is funded by the UK Department for Business, Energy and Industrial Strategy and Department of Biotechnology, Ministry of Science and Technology, Government of India and delivered by the British Council. 
For additional information visit


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Funding Partners

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