Henry Kyalo is a Data Scientist with over four years of experience designing and deploying machine learning and data-driven solutions in research and humanitarian settings. He holds a BSc in Computer Science. His work sits at the intersection of artificial intelligence, Earth Observation, and development practice, with a strong focus on translating advanced analytics into decision making. He has led and contributed to projects such as developing crop systems classification models, Digital Twin framework for push-pull cereal based cropping systems in Kenya that integrates EO, IoT, and AI modelling. He has also deployed machine learning based decision support systems to improve productivity in climate-smart agricultural enterprises, and designed ETL pipelines and scalable data architectures. Currently, he is supporting in building AI-powered public health surveillance and early response system for refugee camps in Kenya. His publications and technical outputs focus on AI-driven crop systems mapping, food security forecasting, and data-informed resilience planning. Henry’s research interests center on AI for Health, AI for Food Security, digital agriculture, and the responsible application of machine learning in fragile and resource-constrained contexts.