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George Dakurah

Geography and Rural Development

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About

Dr George Dakurah is a lecturer at the Department of Geography and Rural Development, Kwame Nkrumah University of Science and Technology (KNUST), Ghana. He has a multi-disciplinary background in Geography (Bachelor’s – University of Ghana), Population Studies (Master’s – University of Ghana), Environment and Development (Master’s – King’s College London, University of London), and a PhD in Livelihoods (International and Rural Development)- University of Reading, United Kingdom (UK).Passionate about research, Dr Dakurah has extensive experience working in research projects with team members from diverse academic, ethnic and spatial backgrounds. For example, he recently worked as a consultant for the Food and Agriculture Organisation (FAO) of the United Nations (UN), on the project "Yenkasa: Towards an Inclusive Communication for Agricultural Development in Africa" where he partnered with staff of the FAO (Rome, Italy), and World Association of Community Radio Broadcasters (AMARC) – Brussels. Similarly, Dr Dakurah has worked with the Earth and Atmospheric laboratory of the Cheikh Anta Diop University (Senegal) to understand how the Senegalese Government managed the Africa Risk Capacity Fund (ARC Fund). To that end, the team wrote an assessment report on how the 2014 drought affected people and livelihoods in Senegal.Dr Dakurah has recently published a paper with Geojournal entitled “How do farmers’ perceptions of climate variability and change match or and mismatch climatic data? Evidence from North-west Ghana” Similarly, he has several papers (e.g. “ We used to ‘chase the rains’ away in the past: cultural values and beliefs, and farmers’ perceptions of climate variability and change in North-west Ghana “ , and “ No sorghum, no funerals among the Dagaaba of North-west Ghana: the cultural aspects of the uses of crops “  that are  been considered for publication in International Peer Reviewed Journals- i.e.  Agriculture and Human Values, and African Studies respectively).

Research Summary

(inferred from publications by AI)

The researcher has explored the transformative application of deep learning across climate-related domains, focusing on how neural networks enable advancements in data analysis, forecasting, and modeling within climatic systems.

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This profile is generated from publicly available publication metadata and is intended for research discovery purposes. Themes, summaries, and trajectories are inferred computationally and may not capture the full scope of the lecturer's work. For authoritative information, please refer to the official KNUST profile.