“Predicting Food Security in Ethiopia Based on Heterogeneous Data.”
Country of Study
Ethiopia
Institution
Bahir Dar Institute of Technology University
Expected Year of Completion
2027
Thematic Area
Agriculture and Food security
Education
Zigju holds a Master of Technology in Computer Science and Engineering from Punjabi University, Patiala, India, which she completed between September 2016 and July 2018. She is currently pursuing a PhD in Data Science at Bahir Dar Institute of Technology, Bahir Dar University, Ethiopia, which she began in November 2022. She has completed her coursework requirements and successfully defended her research proposal. Zigju is in her third year of PhD studies, with an expected dissertation defense date in May 2027 and graduation in June 2027.
Research Summary
Zigju’s research aims to address Ethiopia’s food security challenges by developing predictive models that incorporate heterogeneous data from climate, agriculture, conflict, and socio-economic sources. Given Ethiopia’s vulnerability to food insecurity due to factors like social conflict, climate change, and poor agricultural practices, this study will introduce advanced data preprocessing techniques to handle complex datasets. Using a heterogeneous ensemble model, including Random Forest, XGBoost, Recurrent Neural Networks, and Convolutional Neural Networks, the research aims to generate accurate predictions to help stakeholders make informed decisions. This work will provide valuable insights into the key factors affecting food security, offering a framework that can be applied to other countries facing similar issues.
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