Tumi Samuel-Ipaye is a Data Engineer at the All Lab, specializing in transforming raw data from low-resourced languages into machine-ready formats for AI model development. Her expertise lies in developing efficient methods such as transfer learning-based data augmentation, multilingual embedding alignment, and unsupervised morphological segmentation to clean, ingest, and structure linguistic data. Tumi’s work is crucial in enabling the development of text-to-text translation, speech recognition, and chatbot systems for underrepresented African languages. She is passionate about overcoming the unique challenges of low-resource languages and bridging the gap between raw linguistic data and AI applications.