My research explores the intersection of Natural Language Processing (NLP), Brain science, and Low-Resourced languages, aiming to make these languages more inclusive in neurotechnology innovations. Language is deeply intertwined with cognition, and understanding how the brain processes diverse linguistic structures is crucial for developing AI and brain-computer interfaces (BCIs) that serve all populations, not just those whose languages dominate existing datasets.
Currently, neurotechnology and AI models for language processing are heavily biased toward high-resource languages, leaving out the rich linguistic diversity of low-resource language communities. This exclusion reinforces digital colonialism and limits the potential impact of AI-driven healthcare, education, and accessibility solutions for millions of speakers.
My work focuses on addressing these gaps by:
Exploring data challenges in integrating African languages into NLP models for cognitive and neurological research.
Developing ethical and community-centered approaches for multilingual AI in neurotechnology, ensuring that technological advancements benefit diverse linguistic groups equitably.