Dan is a science professional with a computer science background, and he is advancing his expertise through a master’s program in information systems and IT innovation. Passionate about health, agriculture, and sustainable development, Dan has dedicated his career to creating innovative solutions for critical challenges in these sectors. As a CAN fellow, he will use climate and health datasets to develop a cloud-native machine-learning application to predict respiratory health outcomes in Ghana. This project aims to support early-warning public health outreach and inform policy decisions, contributing to better health resilience in the face of climate change.
