Our research spans multilingual AI, ethical AI, healthcare systems, and domain-specific automation — with publications and open contributions to the African NLP community.
Otoibhi J., et al.
Proceedings of the Sixth Workshop on AfricaNLP 2025 (pp. 95-107). ACL
Otoibhi J.
AI Policy Lab Africa
PEPLER with reparameterization for explainable recommendations
Integration of reparameterization to PEPLER's implementation (DIV-3.55, FCR-0.11, BLEU-4 0.8197)
Automatic Post-Edit (APE) Translator with Online Adaptation
Designed and trained APE model. BLEU-4 0.43, TER 0.66.
Adapting Large Language Models for Collaborative Semantic Recommendations
Modified original implementation to support unique user index generation.
JHU++ Image Crowd Counting (open source implementation)
Implemented a confidence-guided deep residual crowd counting model using PyTorch.
Evaluating Bias in Large Language Models For African Languages
Language bias in LLMs, comparing metrics between African, English and European texts.
Full research profile on the founder page.