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John is currently a Ph.D. student in Applied Mathematics at the University of Rwanda. His research focuses on leveraging machine learning to improve satellite rainfall estimates for African rain-fed agriculture. He obtained a BSc. in Mathematical Science (Mathematics) at the University for Development Studies, Ghana, in 2019, and subsequently obtained an MSc. Mathematical Sciences from AIMS Senegal.
His research interests include Data Science, Machine Learning, Remote Sensing, Climate Change, and Rainfall, and he is passionate about using data, statistics, data science, machine learning, and artificial intelligence to help African rain-fed farmers. He recently interned with the International Crops Research Institute for the Semi-Arid Tropics, ICRISAT, Mali where he researched leveraging machine learning with satellite images for plot delineation in the African rain-fed agriculture setting. In this project, he researched and built a Python package, making use of the deep learning algorithm (UNET) and transfer learning, for detecting plot boundaries.
John is a Co-founder and Team Lead of AI Ghana, a nonprofit organization that seeks to promote the use of Artificial Intelligence in solving problems in Ghana and beyond. John has also served as the Country Ambassador of Zindi (a platform that hosts the largest community of African data scientists, working to solve the world’s most pressing challenges using Machine Learning and AI) since January 2020. Volunteering with AI Ghana and Zindi, he organized the first ever inter-university machine learning hackathon in Ghana (Umoja Hack Ghana 2020) which saw over eight universities participating, and has also organized so many weekend webinars where participants were taken through important concepts in AI, Data Science or Machine Learning either by himself or invited experts. He was also a program committee member of the successfully organized IndabaX Ghana 2021 and oversaw the smooth running of a Zindi machine learning hackathon which was part of the program.
“Extraction and Systematic Synthesis of Textual Information by Contextualization and Enrichment : Applications of Automated Reasoning in the Cognitive Sciences”, “Problem and Solution Documentation Template for Machine Learning Competitions to Enhance Explainability, Reproducibility, and Collaboration Between Stakeholders”, and “Federated Grassroots Community Model for Catalyzing Artificial Intelligence for Common Good”.
John enjoys writing and traveling. He also likes listening to music and playing the trumpet.
Address:
AIMS-NEI Global Secretariat,
District Gasabo,
Secteur Kacyiru,
Cellule Kamatamu Rue KG590 ST,
Kigali, Rwanda
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